- name
- education-data-source-edfacts
- description
- EDFacts — K-12 outcomes: assessment proficiency, ACGR graduation rates, ESSA accountability at school/district level (2009-2020). Within-state trends and subgroup gaps. Complements CCD with outcome data. Cannot compare across states — use NAEP.
- metadata
- {"audience":"any-agent","domain":"data-source","skill-authored":"2026-02-09","skill-last-updated":"2026-02-09"}
# EDFacts Data Source Reference
EDFacts — federal K-12 outcome data from State Education Agencies, covering state assessment proficiency rates, ACGR graduation rates, and ESSA accountability indicators at school and district level (assessments 2009-2020, graduation rates 2010-2019). Use when analyzing within-state achievement trends, subgroup proficiency gaps, or adjusted cohort graduation rates. Complements CCD (school characteristics) with outcome data. State assessment scores CANNOT be compared across states; use NAEP for cross-state comparisons.
EDFacts is the U.S. Department of Education's centralized data collection system for pre-K through grade 12 education data from State Education Agencies (SEAs). It provides state assessment proficiency rates, graduation rates, and accountability indicators — the authoritative federal source for state-level K-12 outcome data.
> **CRITICAL: Value Encoding**
>
> The Urban Institute Education Data Portal converts NCES string codes (e.g., `ALL`, `CWD`, `LEP`) to **integer codes**. Always verify actual data values before filtering — do not rely on documentation labels alone.
>
> | Context | Subgroup "All" | English Learner | Sex "Male" |
> |---------|----------------|-----------------|------------|
> | **Portal integer** | `99` | `1` | `1` |
> | NCES string | `ALL` | `LEP` | `M` |
>
> See `./references/variable-definitions.md` for complete encoding tables.
## What is EDFacts?
- **Collector**: U.S. Department of Education, via State Education Agencies (SEAs)
- **Coverage**: All public schools and districts in 50 states + DC
- **Content**: State assessment proficiency rates, ACGR graduation rates, participation rates, accountability indicators
- **Frequency**: Annual collection
- **Available years**: Assessments 2009-10 to present; Graduation rates 2010-11 to present
- **Primary identifiers**: `ncessch` (school ID, Int64), `leaid` (district ID, Int64), `fips` (state FIPS code, Int64)
- **Key limitation**: State assessment scores CANNOT be compared across states (different tests, different cut scores)
- **Available through**: Education Data Portal mirrors
## Reference File Structure
| File | Purpose | When to Read |
|------|---------|--------------|
| `accountability-context.md` | ESSA, NCLB history, accountability systems | Understanding policy context |
| `assessment-data.md` | Proficiency levels, test scores, limitations | Working with assessment data |
| `graduation-rates.md` | ACGR methodology, cohort definitions | Analyzing graduation data |
| `variable-definitions.md` | Key variables, suppression codes, special values | Interpreting specific variables |
| `data-quality.md` | Known issues, state variations, COVID impacts | Data cleaning, limitations |
| `subgroup-reporting.md` | Special populations, disaggregation | Analyzing by student groups |
## Decision Trees
### What type of analysis?
```
What EDFacts data do you need?
├─ Assessment/proficiency data
│ ├─ Within-state trends → Valid analysis
│ ├─ Cross-state comparison → INVALID - use NAEP instead
│ └─ Subgroup gaps → See ./references/subgroup-reporting.md
├─ Graduation rates (ACGR)
│ ├─ Understand methodology → See ./references/graduation-rates.md
│ ├─ Extended rates (5-year, 6-year) → See ./references/graduation-rates.md
│ └─ Subgroup rates → See ./references/subgroup-reporting.md
├─ Understanding variables
│ ├─ Missing/suppressed values → See ./references/variable-definitions.md
│ ├─ Range vs. exact values → See ./references/variable-definitions.md
│ └─ Subgroup codes → See ./references/subgroup-reporting.md
└─ Data quality concerns
├─ COVID-19 impacts (2019-20) → See ./references/data-quality.md
├─ State reporting changes → See ./references/data-quality.md
└─ Suppression rates → See ./references/data-quality.md
```
### Is my comparison valid?
```
What are you comparing?
├─ Same state, different years
│ ├─ Same assessment system? → Valid
│ └─ Different tests? → Break in time series
├─ Schools within same state → Valid
├─ Districts within same state → Valid
├─ Subgroups within same school → Valid (check suppression)
├─ Different states
│ ├─ Proficiency rates → INVALID
│ ├─ Graduation rates (ACGR) → More comparable
│ └─ Use NAEP instead → Valid
└─ National ranking by proficiency → INVALID
```
## Quick Reference: EDFacts Data Elements
### Assessment Data
| Data Element | Description | Available Years |
|--------------|-------------|-----------------|
| Proficiency rates | % meeting state standards in reading/math | 2009-10 to present |
| Participation rates | % of students assessed | 2012-13 to present |
| Achievement levels | Below Basic, Basic, Proficient, Advanced | Varies by state |
| Grade levels | Grades 3-8, high school (varies) | 2009-10 to present |
### Graduation Data
| Data Element | Description | Available Years |
|--------------|-------------|-----------------|
| 4-year ACGR | Adjusted Cohort Graduation Rate | 2010-11 to present |
| 5-year ACGR | Extended graduation rate | 2011-12 to present |
| 6-year ACGR | Further extended rate | 2012-13 to present |
| Diploma types | Regular diploma only in ACGR | All years |
### Key Identifiers
> **Portal Data Types:** All identifiers are **Int64** in the Portal parquet files. The NCES source format (zero-padded strings) is shown for reference only. When joining with other Portal datasets, join on the integer columns directly.
| ID | Portal Type | NCES Source Format | Level | Example (Int64) |
|----|-------------|-------------------|-------|-----------------|
| `ncessch` | Int64 | 12-char zero-padded | School | `10000500870` |
| `ncessch_num` | Int64 | Same as ncessch | School | `10000500870` |
| `leaid` | Int64 | 7-char zero-padded | District/LEA | `100005` |
| `leaid_num` | Int64 | Same as leaid | District/LEA | `100005` |
| `fips` | Int64 | 2-digit | State | `1` (Alabama) |
### Data Levels
| Level | Identifier | Dataset Path Pattern |
|-------|------------|---------------------|
| School | `ncessch` (Int64) | `edfacts/schools_edfacts_*` |
| District/LEA | `leaid` (Int64) | `edfacts/districts_edfacts_*` |
| State | `fips` (Int64) | Aggregate from lower levels |
### Subgroups Reported
> **Note:** Not all subgroup columns are present in every dataset. Grad rates data does NOT have `sex`, `migrant`, or `military_connected` columns.
| Subgroup | NCES Code | Portal Integer | Column | Available In |
|----------|-----------|----------------|--------|--------------|
| All students | `ALL` | `99` | race, sex, lep, disability | Assessments, Grad Rates |
| Economically disadvantaged | `ECODIS` | `1` | econ_disadvantaged | Assessments, Grad Rates |
| Students with disabilities | `CWD` | `1` | disability | Assessments, Grad Rates |
| English learners | `LEP` | `1` | lep | Assessments, Grad Rates |
| Homeless | `HOM` | `1` | homeless | Assessments, Grad Rates |
| Foster care | `FCS` | `1` | foster_care | Assessments, Grad Rates |
| Migrant | `MIG` | `1` | migrant | Assessments only |
| Military connected | `MIL` | `1` | military_connected | Assessments only |
| Race/ethnicity | Multiple | `1-7, 99` | race | Assessments, Grad Rates |
| Sex | `M/F` | `1, 2, 99` | sex | Assessments only |
**EDFacts Filter Column Pattern:**
- Special population columns (lep, disability, homeless, etc.) use `1` = subgroup, `99` = total
- Race column uses integer codes (1=White, 2=Black, etc.)
- Sex column uses `1` = Male, `2` = Female, `99` = Total (assessments only)
### Grade Codes (grade_edfacts)
| Code | Grade Level |
|------|-------------|
| `3`-`8` | Grades 3-8 (individual) |
| `9` | Grades 9-12 combined |
| `99` | Total (all grades) |
### Race Codes
> **Empirically verified** from 2018 school assessment data. Only these values appear in the `race` column:
| Code | Category |
|------|----------|
| `1` | White |
| `2` | Black |
| `3` | Hispanic |
| `4` | Asian |
| `5` | American Indian/Alaska Native |
| `7` | Two or More Races |
| `99` | Total |
> **Note:** Code `6` (Native Hawaiian/Pacific Islander) is NOT observed in the data. Codes `8` (Nonresident alien), `9` (Unknown), `20` (Other), `-1`, `-2`, `-3` are also not observed in the race column. These codes may exist in other Portal sources but are absent from EDFacts.
### Sex Codes
| Code | Category |
|------|----------|
| `1` | Male |
| `2` | Female |
| `9` | Unknown |
| `99` | Total |
### Disability Codes
> **Empirically verified** from 2018 school assessment and 2019 grad rate data. Only `1` and `99` are observed in the `disability` column. The expanded codes (0-4) documented in other Portal sources are NOT present in EDFacts datasets.
| Code | Category |
|------|----------|
| `1` | Students with disabilities (IDEA-eligible) |
| `99` | Total (all students) |
### LEP Codes
| Code | Category |
|------|----------|
| `1` | Students who are limited English proficient |
| `99` | All students (total) |
### Special Population Columns
For `homeless`, `migrant`, `econ_disadvantaged`, `foster_care`, `military_connected`:
| Code | Category |
|------|----------|
| `1` | Yes (in subgroup) |
| `99` | Total (all students) |
### Missing Data Codes
| Code | Meaning | When Used |
|------|---------|-----------|
| `-1` | Missing/not applicable | Data not reported |
| `-2` | Not reported | Item doesn't apply to this entity |
| `-3` | Suppressed for privacy | Data suppressed for small N-size |
| `-9` | Rounds to zero | Value rounds to zero |
| Range values | Exact value suppressed | Range provided instead of exact value |
| `_midpt` suffix | Calculated midpoint of suppressed range | Use for analysis when exact values are suppressed |
**Always use `_midpt` variables for analysis when exact values are suppressed.**
## Data Access
All EDFacts data is fetched via the **Education Data Portal mirror system**. There is no API access.
**Key references:**
- **`mirrors.yaml`** -- Mirror definitions, URL templates, read strategies
- **`datasets-reference.md`** -- Canonical dataset paths (one path works for all mirrors)
- **`fetch-patterns.md`** -- `fetch_from_mirrors()` and `fetch_yearly_from_mirrors()` patterns
> **Truth Hierarchy:** When interpreting variable values, apply this priority:
> 1. **Actual data file** (what you observe in the parquet/CSV) — this IS the truth
> 2. **Live codebook** (.xls in mirror) — authoritative documentation, may lag
> 3. **This skill documentation** — convenient summary, may drift from codebook
>
> If this documentation contradicts the codebook, trust the codebook. If the codebook contradicts observed data, trust the data and investigate.
### Key Datasets
| Dataset | Path | Type | Columns |
|---------|------|------|---------|
| School Assessments | `edfacts/schools_edfacts_assessments_{year}` | Yearly (2009-2018, 2020) | 26 cols |
| School Grad Rates | `edfacts/schools_edfacts_grad_rates_{year}` | Yearly (2010-2019) | 18 cols |
| District Assessments | `edfacts/districts_edfacts_assessments_{year}` | Yearly (2009-2018, 2020) | 23 cols |
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