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SKILL.md
CCD Data Source Reference
Common Core of Data (CCD) — the federal complete-universe database of all U.S. public K-12 schools and districts (~100,000 schools, ~18,000 districts), collecting enrollment, staffing, finance, and directory data annually (1986-present). Use when analyzing public school enrollment by grade/race/sex, district finances, school staffing, or directory attributes. Public schools and districts only; excludes private schools and postsecondary. Note significant variable encoding and race/ethnicity definition changes over time.
The CCD is the Department of Education's comprehensive, annual, national database of all public elementary and secondary schools and school districts in the United States. It is the only federal dataset that provides a complete universe census (not a sample) of U.S. public K-12 education.
CRITICAL: Value Encoding
The Education Data Portal uses integer codes for categorical variables that
differ from NCES's original string codes. Always verify codes against codebooks.
Context
school_type
charter
urban_centric_locale
Portal (integers)
1 (Regular)
0 (No) / 1 (Yes)
11 (City-Large)
NCES original
1-Regular school
Yes / No
11-City: Large
Note:charter and magnet use 0/1 encoding, NOT 1=Yes / 2=No as some NCES documentation shows.
See ./references/variable-definitions.md for complete encoding tables.
What is CCD?
: DOE's authoritative source for public elementary/secondary education statistics
Primary K-12 database
Universe survey: Covers ALL public schools and districts, not a sample
Annual collection: Data submitted by State Education Agencies (SEAs) each year
Six major components: Directory, Membership, Staffing, Finance (state and district), Dropout/Completers
Coverage: ~100,000 public schools and ~18,000 school districts nationwide
Historical depth: Data available from 1986 to present (varies by component)
Collector: National Center for Education Statistics (NCES) via EDFacts
Available through: Education Data Portal mirrors (5 of 6 survey components; see Data Access section for details)
Reference File Structure
File
Purpose
When to Read
survey-components.md
Detailed coverage of each CCD survey component
Understanding what data is collected
data-collection.md
How data flows from schools to NCES, timelines, respondent universe
Understanding data provenance and timing
variable-definitions.md
Key variables, coding schemes, special values
Interpreting specific data elements
data-quality.md
Missing data patterns, suppression, state variations
Assessing data reliability
historical-changes.md
Definition changes, code revisions over time
Longitudinal analysis
Decision Trees
What CCD component do I need?
What information do you need?
├─ School/district names, addresses, contacts → Directory
│ └─ See ./references/survey-components.md#directory
├─ Student enrollment counts → Membership
│ ├─ By grade → Membership (grade disaggregation)
│ ├─ By race/ethnicity → Membership (race disaggregation)
│ ├─ By sex → Membership (sex disaggregation)
│ └─ See ./references/survey-components.md#membership
├─ Staff/teacher counts → Staffing
│ └─ See ./references/survey-components.md#staffing
├─ Revenue and expenditure → Finance
│ ├─ State-level totals → National Public Education Financial Survey
│ ├─ District-level detail → School District Finance Survey (F-33)
│ └─ See ./references/survey-components.md#finance
├─ Graduation/dropout rates → Dropout and Completers
│ └─ See ./references/survey-components.md#dropout-completers
└─ School type, charter status, locale → Directory
└─ See ./references/survey-components.md#directory
Is this a data quality issue?
Unexpected data values?
├─ Negative numbers (-1, -2, -3, -9) → Missing data codes
│ └─ See ./references/variable-definitions.md#missing-data-codes
├─ Very different from prior year → Check for definition changes
│ └─ See ./references/historical-changes.md
├─ State appears as outlier → Check state-specific reporting
│ └─ See ./references/data-quality.md#state-variations
├─ Large number of zeros → Check suppression rules
│ └─ See ./references/data-quality.md#suppression
└─ Locale codes don't match → Pre/post 2006 locale system change
└─ See ./references/historical-changes.md#locale-codes
Can I compare across time?
Building a time series?
├─ Race/ethnicity categories → Major change in 2010
│ └─ See ./references/historical-changes.md#race-ethnicity
├─ Locale codes → Completely revised in 2006
│ └─ See ./references/historical-changes.md#locale-codes
├─ School/district IDs → Check for ID changes
│ └─ See ./references/variable-definitions.md#identifiers
├─ Free/reduced lunch → CEP and direct certification changes
│ └─ See ./references/data-quality.md#frpl
└─ Finance data → Definition changes and inflation
└─ See ./references/historical-changes.md#finance
Quick Reference: CCD Components
Component
Level
Key Variables
Years
Update Cycle
Directory
School, LEA, State
Name, address, type, status, locale, charter
1986+
Annual
Membership
School, LEA, State
Enrollment by grade, race, sex
1986+
Annual
Staffing
School, LEA, State
FTE teachers, staff by category
1987+
Annual
Finance (State)
State
Revenue, expenditure by source/function
1989+
Annual (1-2 yr lag)
Finance (District)
LEA
Revenue, expenditure, per-pupil
1989+
Annual (2 yr lag)
Dropout/Completers
LEA, State
Dropout counts, diploma recipients
1991+
Annual
Note: Not all components listed above are available through the Portal mirrors. See the Data Access section for which datasets are mirrored.
Key Identifiers
Portal Column
Format
Level
Example
Notes
ncessch
12 characters
School
010000100100
State FIPS (2) + LEA suffix (5) + School (5)
leaid
7 characters
District
0100001
State FIPS (2) + State-assigned (5)
fips
2 digits
State
01
Federal Information Processing Standard
ID Type Warning:ncessch and leaid may be String or Int64 depending on the dataset.
In the Schools Directory, ncessch is String (preserving leading zeros); in enrollment data,
ncessch is Int64. In the Districts Directory, leaid is Int64; in Finance data, leaid is String.
Always check the actual dtype and cast as needed when joining across datasets.
Missing Data Codes
The Portal uses both null and negative integer codes to represent missing/special values. The specific pattern varies by dataset:
Code
Meaning
When Used
null
Not available
Common in Directory fields that don't apply to all years
-1
Missing/not reported
Data not reported by state
-2
Not applicable
Item doesn't apply to this entity
-3
Suppressed
Data suppressed for privacy
-9
Not reported
State did not report this item
Check actual data. Some datasets use null where others use -1 for effectively the same condition. Always check the observed values in the data before applying a blanket missing-value filter.
School Types (school_type)
Code
Type
Description
1
Regular
Standard public school
2
Special Education
Focuses on students with disabilities
3
Vocational
Career/technical education focus
4
Alternative
Non-traditional programs
5
Reportable Program
Program within another school (2007-08+)
LEA Types (agency_type)
Code
Type
Description
1
Regular
Locally governed school district
2
Component
District sharing superintendent with others
3
Supervisory Union
Admin services for multiple districts
4
Regional Agency
Education service agency
5
State-operated
State-run schools (deaf, blind, correctional)
6
Federal-operated
Federal schools (BIE, DoDEA)
7
Charter Agency
All schools are charters (2007-08+)
8
Other
Doesn't fit other categories (2007-08+)
9
Specialized Agency
Specialized public agency (observed in data)
Grade -1 Encoding
In CCD enrollment data:
grade = -1 means Pre-Kindergarten, NOT missing data
grade = 99 means Total across all grades
Do NOT filter grade >= 0 — this removes all Pre-K students!
Variable Name Mapping: The Portal column urban_centric_locale contains locale codes. Some documentation may refer to this as simply locale. Use urban_centric_locale when filtering or selecting columns in Portal data.
Dataset-to-Component Mapping
Mirror Dataset
CCD Component
Path
Schools CCD Directory
School Directory
ccd/schools_ccd_directory
Schools CCD Enrollment
School Membership
ccd/schools_ccd_enrollment_{year}
Districts LEA Directory
LEA Directory
ccd/school-districts_lea_directory
Districts CCD Enrollment
LEA Membership
ccd/schools_ccd_lea_enrollment_{year}
Districts CCD Finance
F-33 District Finance
ccd/districts_ccd_finance
Data Collection Flow
Schools → Local Education Agencies (LEAs)
↓
State Education Agencies (SEAs)
↓
EDFacts Submission System
↓
NCES Quality Review & Editing
↓
CCD Public Data Files
Timeline: Data for school year 20XX-YY typically submitted spring 20YY, released fall 20YY (preliminary) to spring 20YY+1 (provisional/final).
Data Access
Datasets for CCD are available via the mirror system. See datasets-reference.md for canonical paths, mirrors.yaml for mirror configuration, and fetch-patterns.md for fetch code patterns.
Key datasets (5 datasets; see datasets-reference.md for the authoritative list):
Dataset
Type
Path
Codebook
School Directory
Single
ccd/schools_ccd_directory
ccd/codebook_schools_ccd_directory
School Enrollment
Yearly (1986-2023)
ccd/schools_ccd_enrollment_{year}
ccd/codebook_schools_ccd_enrollment
District Directory
Single
ccd/school-districts_lea_directory
ccd/codebook_districts_ccd_directory
District Enrollment
Yearly (1986-2023)
ccd/schools_ccd_lea_enrollment_{year}
ccd/codebook_districts_ccd_enrollment
District Finance
Single
ccd/districts_ccd_finance
ccd/codebook_districts_ccd_finance
Not in Portal mirrors: The following CCD components are documented in this skill for reference but are not available through the Education Data Portal mirrors:
Dropout/Completers — completion and dropout data by demographics
State Finance (NPEFS) — state-level education revenue and expenditure
Truth Hierarchy: When interpreting variable values, apply this priority:
Actual data file (what you observe in the parquet/CSV) -- this IS the truth
Live codebook (.xls in mirror) -- authoritative documentation, may lag
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.
Filtering
All filtering is done locally with Polars after download:
import polars as pl
# Filter by state (California)
df = df.filter(pl.col("fips") == 6)
# Filter by year
df = df.filter(pl.col("year").is_in([2020, 2021, 2022]))
# Get totals only (enrollment)
df = df.filter(pl.col("grade") == 99)
# Get specific grades (K-12)
df = df.filter(pl.col("grade").is_between(0, 12))
Finance Data Notes
Finance data lag: The latest available year in the mirror is 2020 (empirically verified). Finance data typically lags 2+ years behind current school year.
Finance dataset has 163 columns -- by far the most complex CCD dataset
Some finance columns use _total suffix (e.g., exp_current_instruction_total)
leaid is String type in Finance data (unlike the Districts Directory where it is Int64)
Common Pitfalls
Pitfall
Issue
Solution
Summing grades
Misses ungraded students
Use grade=99 (total) instead
Assuming -1 is missing
In grade data, -1 = Pre-K
Check variable format in codebook
Cross-state comparison
Different state definitions
Check state methodology first
Using FRPL as poverty measure
CEP schools show 100%
Supplement with MEPS or SAIPE data
Locale time series
2006 code system change
Analyze pre/post-2006 separately
Charter school counts
Early years incomplete
Verify against state records pre-2010
Dropout rate comparison
State definitions vary
Within-state comparisons only
Using NCES string codes
Portal uses integers
See variable-definitions.md for mappings
Assuming charter=1/2
Portal uses 0=No, 1=Yes
Empirically verified; not NCES 1=Yes, 2=No
ID type across datasets
leaid/ncessch may be String or Int64
Always check dtype before joining
Coverage Notes
What CCD Includes
All public schools (traditional, charter, magnet, alternative)
All public school districts and LEAs
Bureau of Indian Education (BIE) schools
Department of Defense Education Activity (DoDEA) schools
