Education Data Explorer

Discover available education data from the Urban Institute Education Data Portal for research planning and query design.

What is the Education Data Portal?

• •Comprehensive education data from Urban Institute - free and publicly available
• •Three data levels: schools, school-districts, college-university
• •Multiple data sources: CCD, IPEDS, CRDC, College Scorecard, EDFacts, SAIPE, FSA, MEPS, PSEO, etc.
• •Coverage: 1980-2023 depending on source
• •Access: Mirror downloads (parquet/CSV) via education-data-query skill
• •Documentation: https://educationdata.urban.org/documentation/

Note: This workflow uses mirror-based file downloads, not paginated API calls. See education-data-query skill for fetch patterns and datasets-reference.md for file paths.

Reference File Structure

Decision Trees

What data level do I need?

What entity am I researching?
├─ Individual K-12 schools → schools level
│   └─ See ./references/schools-endpoints.md
├─ School districts / LEAs → school-districts level
│   └─ See ./references/districts-endpoints.md
├─ Colleges / Universities → college-university level
│   └─ See ./references/colleges-endpoints.md
└─ Not sure
    ├─ Need school-specific data (discipline, AP, demographics) → schools
    ├─ Need aggregate district data (finance, poverty) → school-districts
    └─ Need postsecondary data (enrollment, aid, outcomes) → college-university

What topic am I researching?

Research topic?
├─ Enrollment / Demographics
│   ├─ K-12 public schools → CCD enrollment endpoints
│   ├─ Civil rights indicators → CRDC enrollment
│   └─ Colleges → IPEDS enrollment
├─ School Finance
│   ├─ District revenue/expenditure → CCD finance
│   └─ College finance → IPEDS finance
├─ Student Outcomes
│   ├─ K-12 assessments → EDFacts
│   ├─ Graduation rates (K-12) → EDFacts
│   ├─ College completion → IPEDS completions
│   └─ Post-college earnings → College Scorecard
├─ Student Aid / Loans
│   ├─ College financial aid → IPEDS aid
│   ├─ Federal loans/grants → FSA
│   └─ Debt/repayment → College Scorecard
├─ Discipline / Civil Rights
│   └─ K-12 discipline, harassment, restraint → CRDC
├─ Poverty Estimates
│   └─ District-level → SAIPE
└─ Directory / Location
    ├─ K-12 schools → CCD directory
    ├─ Districts → CCD directory
    └─ Colleges → IPEDS directory

How do I find specific variables?

Finding variables?
├─ Know the endpoint → Check reference file for variable list
├─ Know the topic → Use topic index below
├─ Need to search programmatically → See ./references/metadata-api.md
└─ Need code definitions → See ./references/variable-codes.md

Quick Reference: Data Levels

Quick Reference: Data Sources

Quick Reference: Common Endpoints

Schools

Districts

Colleges

Exploration Workflow

Follow these steps to identify data for a research question:

1. •

   Identify data level

   • •Schools: individual K-12 school records
   • •Districts: school district / LEA records
   • •Colleges: postsecondary institution records
2. •

   Identify relevant data source(s)

   • •Use the data sources table above
   • •Multiple sources may be needed (e.g., CCD + CRDC)
3. •

   Check available endpoints

   • •Read the appropriate reference file
   • •Note endpoint URL pattern and variables
4. •

   Review variables and filters

   • •Check variable lists in reference files
   • •Note which variables can be used as filters
5. •

   Check years available

   • •Each endpoint has different year coverage
   • •Use metadata API to get exact years
6. •

   Understand source context (RECOMMENDED)

   • •Load the appropriate education-data-source-* skill for deep context
   • •Understand data collection methodology and limitations
   • •Review variable definitions and coding schemes
7. •

   Plan query

   • •Load education-data-query skill for query construction
   • •Or use metadata API to build query programmatically

URL Pattern Structure

All endpoints follow this pattern:

/api/v1/{level}/{source}/{topic}/{year}/[{disaggregation}/]

Examples:

• •/api/v1/schools/ccd/directory/2022/
• •/api/v1/schools/ccd/enrollment/2022/grade-5/
• •/api/v1/schools/ccd/enrollment/2022/grade-5/race/
• •/api/v1/school-districts/ccd/finance/2021/
• •/api/v1/college-university/ipeds/fall-enrollment/2022/undergraduate/

Filtering

Query Parameters

Response Format

{
  "count": 12345,
  "next": "https://educationdata.urban.org/api/v1/...?page=2",
  "previous": null,
  "results": [
    {"ncessch": "...", "school_name": "...", ...},
    ...
  ]
}

Cross-Reference to Related Skills

Deep-Dive Data Source Skills

For comprehensive understanding of each data source beyond the portal documentation, load the appropriate source-specific skill:

When to load source skills:

• •Need deeper understanding of data collection methodology
• •Encountering unexpected values or patterns
• •Planning analysis that requires understanding source limitations
• •Working with less common data elements not covered in this skill

Topic Index

Example: Planning a Research Query

Research question: "What is the relationship between school poverty and AP course offerings in California high schools?"

1. •

   Data level: Schools (individual school records)

2. •

   Data sources needed:

   • •CRDC for AP course data
   • •MEPS or CCD for poverty measure
3. •

   Endpoints:

   • •/schools/crdc/ap-ib-enrollment/{year}/race/sex/ - AP enrollment (requires disaggregation)
   • •/schools/meps/{year}/ - School poverty measure
4. •

   Key variables:

   • •ncessch - school identifier (for joining)
   • •fips=6 - California filter
   • •AP enrollment variables from CRDC
   • •Poverty measure from MEPS
5. •

   Years: Check overlap (CRDC: 2011-2021, MEPS: 2006-2019)

6. •

   Next step: Load education-data-query skill to construct the actual API calls

Common Pitfalls

• •Year coverage varies: Always check years available for each endpoint
• •Different ID formats: ncessch (12-char), leaid (7-char), unitid (6-digit)
• •Disaggregation in URL: Grade, race, sex are often URL path components, not query params
• •Missing data codes: -1, -2, -3 have specific meanings (see variable-codes.md)

Pre-Query Validation

CRITICAL: Variable Name Discrepancies

The Education Data Portal API often uses different variable names than documentation suggests. Always fetch a sample first:

# Test query to verify actual column names
response = requests.get(
    "https://educationdata.urban.org/api/v1/college-university/ipeds/directory/2023/"
)
data = response.json()
print("Actual columns:", list(data['results'][0].keys()))

Known discrepancies:

See the relevant education-data-source-* skill for comprehensive variable mappings per source.

Metadata API Limitations

The metadata API has undocumented limitations:

• •?section=schools works to filter by data level
• •?source=ipeds does NOT work - filter client-side instead
• •Response field names differ: source is actually class_name, source_name is actually label

Data Source Details

Quick summaries below. For comprehensive documentation including methodology, variable definitions, data quality issues, and historical changes, load the corresponding education-data-source-* skill.

CCD (Common Core of Data)

Coverage: All public elementary and secondary schools and districts in the U.S.

Key Variables:

• •ncessch: 12-character NCES school ID
• •leaid: 7-character NCES district ID
• •enrollment: Total enrollment count
• •free_or_reduced_price_lunch: FRPL-eligible students (poverty proxy)
• •charter: Charter school indicator
• •urban_centric_locale: Urban/suburban/town/rural classification

Deep dive: Load education-data-source-ccd for survey components, data collection process, variable coding, state variations, and historical changes (e.g., 2006 locale code revision, 2010 race category changes).

CRDC (Civil Rights Data Collection)

Coverage: Biennial survey of public schools (2011, 2013, 2015, 2017, 2020, 2021)

Topics:

• •Discipline (suspensions, expulsions, arrests)
• •Chronic absenteeism
• •Harassment and bullying
• •Restraint and seclusion
• •Advanced courses (AP, IB, gifted)
• •Course offerings
• •Teacher qualifications
• •Retention
• •COVID impacts (2020 only)

Key Feature: Disaggregation by race, sex, disability, and LEP status

Deep dive: Load education-data-source-crdc for civil rights legal context (Title VI, IX, Section 504), collection methodology, underreporting issues, and year-to-year changes.

EDFacts

Coverage: State assessment and accountability data

Topics:

• •Assessment proficiency rates (reading, math)
• •Graduation rates (4-year adjusted cohort)

Key Feature: Data available by special populations (disability, economically disadvantaged, LEP, homeless, migrant, foster care)

CRITICAL: State assessment scores CANNOT be compared across states (different tests, cut scores).

Deep dive: Load education-data-source-edfacts for ESSA/NCLB accountability context, why cross-state comparison is invalid, ACGR methodology, and subgroup reporting rules.

IPEDS (Integrated Postsecondary Education Data System)

Coverage: All Title IV-eligible postsecondary institutions

Topics:

• •Institutional characteristics and directory
• •Admissions and enrollment
• •Student charges (tuition, fees, room, board)
• •Financial aid
• •Finance (revenue, expenditure, assets)
• •Graduation rates
• •Completions (degrees awarded by CIP code)
• •Human resources (salaries, faculty)

Key Variables:

• •unitid: 6-digit IPEDS institution ID
• •inst_control: 1=Public, 2=Private nonprofit, 3=Private for-profit
• •institution_level: 1=Less-than-2-year, 2=2-year, 4=4-year (no code 3)
• •hbcu: Historically Black college indicator

Deep dive: Load education-data-source-ipeds for critical graduation rate limitations (first-time full-time only), GASB vs FASB finance accounting, survey components, and identifier changes.

College Scorecard

Coverage: Title IV institutions with outcome data

Topics:

• •Post-college earnings (6 and 10 years after entry)
• •Student debt and repayment
• •Default rates
• •Completion rates by income level

Key Feature: Links education to labor market outcomes

CRITICAL: Only covers Title IV aid recipients (selection bias toward lower-income students).

Deep dive: Load education-data-source-scorecard for earnings methodology (IRS data), population coverage limitations, suppression rules, and field-of-study data.

SAIPE (Small Area Income and Poverty Estimates)

Coverage: Census Bureau poverty estimates for school districts

Key Variables:

• •population_5_17_poverty: Children 5-17 in poverty
• •population_5_17_poverty_pct: Percent in poverty
• •median_household_income: District median income

Deep dive: Load education-data-source-saipe for model-based estimation methodology, confidence intervals (not available at district level), and comparison to other poverty measures.

FSA (Federal Student Aid)

Coverage: Title IV institutions receiving federal aid

Topics:

• •Pell grants
• •Direct loans (subsidized, unsubsidized, PLUS)
• •Campus-based aid (Perkins, work-study)
• •Financial responsibility scores
• •90/10 revenue (for-profit institutions)

Deep dive: Load education-data-source-fsa for Title IV program details, financial responsibility composite scores, and 90/10 rule compliance.

Additional Data Sources

Joining Data Across Sources

School-Level Joins

Join school data across sources using ncessch:

Note: Match on year when joining (years may not align perfectly)

District-Level Joins

Join district data using leaid:

College-Level Joins

Join college data using unitid:

Disaggregation Patterns

URL Path Disaggregation

Some disaggregations are part of the URL path:

/schools/ccd/enrollment/{year}/{grade}/           # By grade
/schools/ccd/enrollment/{year}/{grade}/race/      # By grade and race
/schools/ccd/enrollment/{year}/{grade}/race/sex/  # By grade, race, and sex

Query Parameter Disaggregation

Other filters are query parameters:

?fips=6                    # California only
?charter=1                 # Charter schools only
?school_level=3            # High schools only
?urban_centric_locale=11   # Large cities only

Available Disaggregations by Source

Year Coverage Quick Reference

Example Research Scenarios