🎓 `edu`¶

Institutional education data for K-12 districts, schools, and higher education. K-12 tables cover NCES Common Core of Data (CCD), Civil Rights Data Collection (CRDC), and NAEP assessments. Higher-ed tables cover IPEDS directory, completions, financials, and College Scorecard outcomes. All sourced via the Urban Institute Education Data Portal API (free, unauthenticated) except College Scorecard (free API key required). Complements census.acs_education (population attainment) — this schema describes the institutions themselves.

23 datasets · 271 columns

ccd_districts · table¶

NCES Common Core of Data — Local Education Agency (district) directory. One row per LEA per school year (year = end year; 2022 = 2021-22). Primary join target for ccd_schools (leaid) and geo.school_districts (sd_lea = leaid). Staff FTE fields (teachers, counselors, psychologists) enable resource equity analysis.

Column	Type	Null	Description
`leaid`	string	no	NCES LEA ID (7-digit string) — PK component
`year`	int	no	School year end year (e.g. 2022 = 2021-22) — PK component
`lea_name`	string	yes	District name
`fips`	int	yes	State FIPS code (integer 1-56) — FK to geo.states.state_fips
`state_abbr`	string	yes	2-letter state abbreviation from state_location field
`county_code`	string	yes	County FIPS, zero-padded to 5 chars by the transformer (e.g. '06037') — FK to geo.counties.county_fips
`county_name`	string	yes	County name
`urban_centric_locale`	int	yes	NCES locale code (11=city large, 12=city mid, 13=city small, 21=suburb large, 31=town fringe, 41=rural fringe)
`cbsa`	int	yes	Core-Based Statistical Area code
`latitude`	double	yes	LEA mailing address latitude
`longitude`	double	yes	LEA mailing address longitude
`agency_type`	int	yes	1=local, 2=supervisory union component, 3=state agency, 4=federal, 7=independent charter
`agency_level`	int	yes	1=elementary, 2=secondary, 3=K-12, 4=other
`agency_charter_indicator`	int	yes	1=charter LEA, 0=not charter
`lowest_grade_offered`	int	yes	Lowest grade offered (-1=PK, 0=K, 1-12)
`highest_grade_offered`	int	yes	Highest grade offered
`number_of_schools`	int	yes	Number of operational schools in LEA
`enrollment`	int	yes	Total student enrollment (may be null for some administrative LEAs)
`spec_ed_students`	int	yes	Students receiving special education services
`english_language_learners`	int	yes	English language learner students
`teachers_total_fte`	double	yes	Total FTE classroom teachers across all grade levels
`guidance_counselors_total_fte`	double	yes	Total FTE guidance counselors
`school_counselors_fte`	double	yes	FTE school counselors
`school_psychologists_fte`	double	yes	FTE school psychologists
`librarian_specialists_fte`	double	yes	FTE librarian/media specialists
`staff_total_fte`	double	yes	Total FTE all staff categories
`state_leg_district_lower`	string	yes	State lower legislative district
`state_leg_district_upper`	string	yes	State upper legislative district
`congress_district_id`	int	yes	Congressional district ID

ccd_schools · table¶

NCES Common Core of Data — individual school directory. One row per school per year. Joins to ccd_districts via leaid. free_or_reduced_price_lunch enables poverty proxy at the school level. Biennial CRDC data joins via ncessch = crdc_schools.ncessch.

Column	Type	Null	Description
`ncessch`	string	no	NCES school ID (12-digit string) — PK component
`leaid`	string	no	Parent LEA ID (7-digit) — FK to ccd_districts.leaid
`year`	int	no	School year end year — PK component
`school_name`	string	yes	School name
`fips`	int	yes	State FIPS (integer) — FK to geo.states.state_fips
`county_code`	string	yes	County FIPS, zero-padded to 5 chars by the transformer (e.g. '06037') — FK to geo.counties.county_fips
`latitude`	double	yes	School latitude
`longitude`	double	yes	School longitude
`urban_centric_locale`	int	yes	NCES locale code
`cbsa`	string	yes	CBSA code (string in API)
`school_level`	int	yes	1=elementary, 2=middle, 3=high, 4=other combined
`school_type`	int	yes	1=regular, 2=special ed, 3=vocational, 4=alternative
`school_status`	int	yes	1=open, 2=closed, 3=new, 4=added, 5=changed agency, 6=reopened, 8=future
`lowest_grade_offered`	int	yes	Lowest grade (-1=PK, 0=K, 1-12)
`highest_grade_offered`	int	yes	Highest grade offered
`charter`	int	yes	Charter school indicator (1=yes, 0=no)
`magnet`	int	yes	Magnet school indicator (1=yes, 0=no)
`virtual`	int	yes	Virtual school indicator (1=yes, 0=no, 2=supplemental)
`shared_time`	int	yes	Shared-time school (students also attend another school)
`title_i_status`	int	yes	Title I status code (5=schoolwide, 6=targeted assistance, 7=eligible not participating)
`title_i_eligible`	int	yes	Title I eligible (1=yes, 0=no)
`title_i_schoolwide`	int	yes	Schoolwide Title I program (1=yes, 0=no)
`teachers_fte`	double	yes	FTE classroom teachers
`enrollment`	int	yes	Total student enrollment
`free_lunch`	int	yes	Students approved for free lunch (NSLP)
`reduced_price_lunch`	int	yes	Students approved for reduced-price lunch
`free_or_reduced_price_lunch`	int	yes	Combined free+reduced lunch count; divide by enrollment for poverty proxy
`direct_certification`	int	yes	Students directly certified for free meals (SNAP/TANF households)
`lunch_program`	int	yes	Lunch program type code
`bureau_indian_education`	int	yes	Bureau of Indian Education school indicator
`congress_district_id`	int	yes	Congressional district
`state_leg_district_lower`	string	yes	State lower legislative district
`state_leg_district_upper`	string	yes	State upper legislative district

naep_scores · table¶

NAEP (National Assessment of Educational Progress) state-level results. One row per state × year × subject × grade × subgroup. jurisdiction=0 is the national aggregate. Joins to ccd_districts via fips=state_fips. Available biennially (even years for grade 4/8 main NAEP).

Column	Type	Null	Description
`jurisdiction`	int	no	State FIPS code (0 = national aggregate) — PK component
`jurisdiction_name`	string	yes	State name or "National"
`year`	int	no	Assessment year — PK component
`subject`	string	no	MAT=mathematics, RED=reading — PK component
`grade`	int	no	4 or 8 — PK component
`variable_type`	string	no	Disaggregation type (TOTAL, Race/Ethnicity, Gender, NAEP Eligibility) — PK component
`subgroup_name`	string	no	Subgroup label (All students, Male, White, Black, etc.) — PK component
`avg_score`	double	yes	Average NAEP scale score
`is_displayable`	int	yes	1 if statistically displayable (sufficient sample size)

naep_achievement_levels · table¶

NAEP proficiency level distributions sourced from GetAdhocData ALD stattype calls. One row per state × year × subject × grade × subgroup × level. level values: below_basic, basic, proficient, advanced. pct is the percentage of students at that level for the given key. Joins to naep_scores via (jurisdiction, year, subject, grade, variable_type, subgroup_name).

Column	Type	Null	Description
`jurisdiction`	int	no	State FIPS code (0 = national aggregate) — PK component
`jurisdiction_name`	string	yes	State name or "National"
`year`	int	no	Assessment year — PK component
`subject`	string	no	MAT=mathematics, RED=reading — PK component
`grade`	int	no	4 or 8 — PK component
`variable_type`	string	no	Disaggregation type (TOTAL, Race/Ethnicity, Gender, NAEP Eligibility) — PK component
`subgroup_name`	string	no	Subgroup label (All students, Male, White, Black, etc.) — PK component
`level`	string	no	Proficiency level — PK component; below_basic, basic, proficient, advanced
`pct`	double	yes	Percentage of students at this proficiency level
`is_displayable`	int	yes	1 if statistically displayable

crdc_schools · table¶

CRDC school-level equity data consolidated from four Urban Institute sub-endpoints. crdc_topic dimension selects the sub-endpoint: directory, chronic-absenteeism, offenses, teachers-staff. Join to ccd_schools via ncessch. crdc_id = ncessch for most schools. Available biennially (2013, 2015, 2017, 2020, 2021); 2021 is latest.

Column	Type	Null	Description
`crdc_id`	string	yes	Best available PK component for CRDC records; more properly an AK (alternate key). Equals ncessch for schools in the NCES universe. Chronic-absenteeism pre-2022 data may be null (transformer backfills from ncessch). For schools outside NCES (private/charter), crdc_id is the only identifier; ncessch will be null instead.
`ncessch`	string	yes	NCES school ID — FK to ccd_schools.ncessch; null for ~1,800 non-NCES schools
`leaid`	string	yes	LEA ID — FK to ccd_districts.leaid
`fips`	int	yes	State FIPS
`year`	int	no	Survey year (2011, 2013, 2015, 2017) — PK component
`crdc_topic`	string	no	Sub-endpoint dimension: directory, chronic-absenteeism, offenses, teachers-staff — PK component
`charter_crdc`	int	yes	Charter school per CRDC report (may differ from CCD value)
`magnet_crdc`	int	yes	Magnet school per CRDC
`alt_school`	int	yes	Alternative school indicator
`primarily_serve_students_w_dis`	int	yes	School primarily serves students with disabilities
`race`	string	yes	Race/ethnicity disaggregation (HI=Hispanic, BL=Black, WH=White, etc.; MF=all)
`sex`	string	yes	Sex disaggregation (M=male, F=female, MF=both)
`disability`	string	yes	Disability status disaggregation (WD=with disability, WOD=without, TOT=total)
`lep`	string	yes	Limited English proficiency disaggregation
`students_chronically_absent`	int	yes	Count of chronically absent students (>10% days missed) for this subgroup
`firearm_incident_ind`	int	yes	Any firearm incident reported (0/1)
`homicide_ind`	double	yes	Homicide incident indicator
`rape_incidents`	double	yes	Number of rape allegations
`sexual_battery_incidents`	double	yes	Number of sexual battery incidents
`attack_w_weapon_incidents`	double	yes	Attacks with a weapon (non-firearm)
`attack_no_weapon_incidents`	double	yes	Attacks without a weapon
`possession_firearm_incidents`	double	yes	Firearm possession incidents
`teachers_fte_crdc`	double	yes	Total FTE teachers per CRDC report
`teachers_certified_fte`	double	yes	FTE certified teachers
`teachers_uncertified_fte`	double	yes	FTE uncertified/emergency-certified teachers
`counselors_fte`	double	yes	FTE school counselors
`psychologists_fte`	double	yes	FTE school psychologists
`social_workers_fte`	double	yes	FTE school social workers
`nurses_fte`	double	yes	FTE nurses
`security_guard_fte`	double	yes	FTE security guards
`law_enforcement_fte`	double	yes	FTE sworn law enforcement officers

ipeds_institutions · table¶

NCES IPEDS Institutional Characteristics (HD survey) directory. One row per institution per year. Joins to geo.counties via county_fips (pad integer to 5-char string). Enrollment is NOT here (IPEDS EF survey). Tuition/fees are NOT here — see ipeds_tuition table (academic-year-tuition endpoint). college_scorecard joins via unitid = college_scorecard.id. ipeds_completions and ipeds_financials join via unitid.

Column	Type	Null	Description
`unitid`	int	no	IPEDS unit ID (integer) — PK component
`opeid`	string	yes	OPE ID 8-digit — parent key for college_scorecard.ope8_id (that child declares the FK)
`year`	int	no	Survey year — PK component
`inst_name`	string	yes	Institution name (INSTNM in bulk CSV)
`inst_alias`	string	yes	Institution alias or common name
`address`	string	yes	Street address
`city`	string	yes	City
`state_abbr`	string	yes	State abbreviation — FK to geo.states.state_abbr
`zip`	string	yes	ZIP code
`fips`	int	yes	State FIPS (integer) — FK to geo.states.state_fips
`county_fips`	int	yes	County FIPS integer (COUNTYCD in bulk); source for county_fips_str
`county_fips_str`	string	yes	County FIPS zero-padded to 5 chars (e.g. '06037') — FK to geo.counties.county_fips
`county_name`	string	yes	County name
`longitude`	double	yes	Longitude (LONGITUD in bulk CSV)
`latitude`	double	yes	Latitude
`sector`	int	yes	0=admin, 1=public 4yr, 2=private nonprofit 4yr, 3=private for-profit 4yr, 4=public 2yr, 5=private nonprofit 2yr, 6=private for-profit 2yr, 7=public <2yr, 8=private nonprofit <2yr, 9=private for-profit <2yr
`inst_control`	int	yes	1=public, 2=private nonprofit, 3=private for-profit
`institution_level`	int	yes	1=4yr or higher, 2=2-4yr, 3=<2yr
`hbcu`	int	yes	Historically Black College or University (1=yes, 0=no)
`hospital`	int	yes	Institution has hospital (1=yes, 0=no)
`medical_degree`	int	yes	Medical degree offered (1=yes, 0=no)
`tribal_college`	int	yes	Tribal college or university (1=yes, 0=no)
`land_grant`	int	yes	Land-grant institution (1=yes, 0=no)
`inst_size`	int	yes	1=<1000 students, 2=1000-4999, 3=5000-9999, 4=10000-19999, 5=20000+
`degree_granting`	int	yes	Degree-granting institution (1=yes, 0=no)
`title_iv_indicator`	int	yes	Title IV federal financial aid eligible
`offering_undergrad`	int	yes	Undergraduate programs offered (1=yes)
`offering_grad`	int	yes	Graduate programs offered (1=yes)
`cc_basic_2021`	int	yes	Carnegie Classification basic 2021 (integer code; see carnegie.edu for legend)
`cbsa`	int	yes	CBSA code
`cbsa_type`	int	yes	1=metropolitan, 2=micropolitan
`url_school`	string	yes	Institution website URL

ipeds_completions · table¶

NCES IPEDS Completions survey (C_A bulk CSV). One row per (unitid, year, cipcode, majornum, award_level). Race/ethnicity and sex counts are wide columns (ctotalt, caiant, casiat, cbkaat, chispt, cnhpit, cwhitt, c2mort, cunknt, cnralt and per-sex _m/_w variants). cipcode is the full 6-digit dotted string (e.g. "52.0101"). Source: nces.ed.gov/ipeds/datacenter/data/C{year}_A.zip. Available 2010–present.

Column	Type	Null	Description
`unitid`	int	no	IPEDS unit ID — PK component; FK to ipeds_institutions.unitid
`year`	int	no	Award year — PK component; injected from URL dimension
`cipcode`	string	no	6-digit CIP field of study (e.g. "52.0101") — PK component
`majornum`	int	no	1=first major, 2=second major — PK component
`award_level`	int	no	IPEDS award level — PK component; 1=<1yr cert, 2=1-2yr cert, 3=Associate, 5=Bachelor's, 7=Master's, 17=Doctoral research, 18=Doctoral professional, 19=Doctoral other
`ctotalt`	int	yes	Total completions (all races, both sexes)
`ctotalm`	int	yes	Total completions — men
`ctotalw`	int	yes	Total completions — women
`caiant`	int	yes	American Indian/Alaska Native — total
`caianm`	int	yes	American Indian/Alaska Native — men
`caianw`	int	yes	American Indian/Alaska Native — women
`casiat`	int	yes	Asian — total
`casiam`	int	yes	Asian — men
`casiaw`	int	yes	Asian — women
`cbkaat`	int	yes	Black or African American — total
`cbkaam`	int	yes	Black or African American — men
`cbkaaw`	int	yes	Black or African American — women
`chispt`	int	yes	Hispanic or Latino — total
`chispm`	int	yes	Hispanic or Latino — men
`chispw`	int	yes	Hispanic or Latino — women
`cnhpit`	int	yes	Native Hawaiian/Other Pacific Islander — total
`cnhpim`	int	yes	Native Hawaiian/Other Pacific Islander — men
`cnhpiw`	int	yes	Native Hawaiian/Other Pacific Islander — women
`cwhitt`	int	yes	White — total
`cwhitm`	int	yes	White — men
`cwhitw`	int	yes	White — women
`c2mort`	int	yes	Two or more races — total
`c2morm`	int	yes	Two or more races — men
`c2morw`	int	yes	Two or more races — women
`cunknt`	int	yes	Race/ethnicity unknown — total
`cunknm`	int	yes	Race/ethnicity unknown — men
`cunknw`	int	yes	Race/ethnicity unknown — women
`cnralt`	int	yes	Nonresident alien — total
`cnralm`	int	yes	Nonresident alien — men
`cnralw`	int	yes	Nonresident alien — women

ipeds_financials · table¶

NCES IPEDS Finance survey (F survey). Revenues, expenditures, endowment, and net position per institution per fiscal year. Sourced from NCES bulk ZIP downloads (nces.ed.gov/ipeds/datacenter/data/). Three form_type variants cover all institutions: F1A=GASB public, F2=FASB larger private, F3=FASB smaller private non-profit. All monetary values in dollars. Transformer maps NCES coded column names to canonical names. FY2022-23 is provisional (flag with is_provisional=true); FY2021-22 is the most recent final release. Joins to ipeds_institutions via unitid.

Column	Type	Null	Description
`unitid`	int	no	IPEDS unit ID — PK component; FK to ipeds_institutions.unitid
`year`	int	no	Fiscal year end (end year of academic year, e.g. 2022 = FY2021-22) — PK component
`form_type`	string	no	NCES form variant — PK component; F1A=GASB public, F2=FASB larger private, F3=FASB smaller private
`is_provisional`	int	no	1 if this is a provisional release (FY2022-23 and later); 0 if final
`rev_tuition_fees_gross`	double	yes	Gross tuition and fees revenue before allowances
`rev_tuition_fees_net`	double	yes	Net tuition and fees revenue after discounts/allowances
`rev_appropriations_state`	double	yes	State appropriations revenue
`rev_appropriations_fed`	double	yes	Federal appropriations revenue
`rev_grants_contracts_federal`	double	yes	Federal grants and contracts revenue
`rev_grants_contracts_state`	double	yes	State grants and contracts revenue
`rev_fed_approps_grants`	double	yes	Combined federal appropriations + grants revenue
`rev_state_local_approps_grants`	double	yes	Combined state/local appropriations + grants revenue
`rev_gifts_grants_contracts`	double	yes	Private gifts, grants, and contracts revenue
`rev_investment_return`	double	yes	Return on investments and endowment
`rev_auxiliary_enterprises_net`	double	yes	Auxiliary enterprises net revenue (housing, dining, bookstore)
`rev_operating`	double	yes	Total operating revenues
`rev_nonoperating`	double	yes	Total nonoperating revenues
`rev_total_current`	double	yes	Total all revenues and additions
`sch_pell_grant`	double	yes	Pell grant scholarships/fellowships
`sch_grants_institutional`	double	yes	Unrestricted institutional grants awarded
`sch_total_student_aid`	double	yes	Total student aid awarded
`sch_allowances_tuition_fees`	double	yes	Discount/allowance applied to tuition and fees
`exp_instruc_total`	double	yes	Instruction expenditures total
`exp_research_total`	double	yes	Research expenditures total
`exp_pub_serv_total`	double	yes	Public service expenditures total
`exp_acad_supp_total`	double	yes	Academic support expenditures (libraries, computing, curriculum)
`exp_student_serv_total`	double	yes	Student services expenditures (admissions, registrar, athletics)
`exp_inst_supp_total`	double	yes	Institutional support expenditures (executive management, finance, HR)
`exp_aux_ent_total`	double	yes	Auxiliary enterprises expenditures
`exp_net_grant_aid_total`	double	yes	Net grant aid and fellowships expenditures
`exp_total_current`	double	yes	Total expenses and deductions
`exp_total_salaries`	double	yes	Total salary expenditures across all functions
`endowment_beg`	double	yes	Endowment assets beginning of year
`endowment_end`	double	yes	Endowment assets end of year
`assets`	double	yes	Total assets
`liabilities`	double	yes	Total liabilities
`net_position_end`	double	yes	Net position / net assets at end of year
`longterm_debt`	double	yes	Long-term debt outstanding

ipeds_tuition · table¶

NCES IPEDS IC_AY (Institutional Characteristics — Academic Year) survey. Published tuition and fees by institution, level of study, and tuition type. One row per (unitid, year, level_of_study, tuition_type). level_of_study: 1=undergraduate, 2=graduate. tuition_type: 1=in-district, 2=in-state, 3=out-of-state, 4=out-of-district. Use tuition_type=2 for in-state and tuition_type=3 for out-of-state comparisons.

Column	Type	Null	Description
`unitid`	int	no	IPEDS unit ID — PK component; FK to ipeds_institutions.unitid
`year`	int	no	Academic year — PK component
`fips`	int	yes	State FIPS (denormalized)
`level_of_study`	int	no	1=undergraduate, 2=graduate — PK component
`tuition_type`	int	no	1=in-district, 2=in-state, 3=out-of-state, 4=out-of-district — PK component
`tuition_fees_ft`	int	yes	Full-time tuition and fees (combined)
`tuition_ft`	int	yes	Full-time tuition only
`fees_ft`	int	yes	Full-time required fees only
`credit_hour_charge_pt`	int	yes	Per-credit-hour charge for part-time students
`tuition_published`	int	yes	Published (sticker) tuition
`fees_published`	int	yes	Published required fees
`tuition_fees_published`	int	yes	Published total tuition and fees

college_scorecard · table¶

Dept of Ed College Scorecard institution-level outcomes. Earnings, debt, completion rates, and enrollment demographics. One row per institution per vintage year. Joins to ipeds_institutions via id=unitid or ope8_id=opeid. API key required (API_DATA_GOV); PrivacySuppressed values are null. Earnings field is mean (not median) at 10yr — median available at 8yr.

Column	Type	Null	Description
`id`	int	no	IPEDS unit ID — PK component; FK to ipeds_institutions.unitid
`ope8_id`	string	yes	OPE ID 8-digit — FK to ipeds_institutions.opeid
`ope6_id`	string	yes	OPE ID 6-digit
`year`	int	no	Data vintage year — PK component
`name`	string	yes	Institution name (school.name)
`city`	string	yes	City
`state`	string	yes	State abbreviation — FK to geo.states.state_abbr
`ownership`	int	yes	1=public, 2=private nonprofit, 3=private for-profit
`carnegie_basic`	int	yes	Carnegie basic classification (integer code)
`hbcu`	int	yes	HBCU flag (1=yes)
`tribal`	int	yes	Tribal college flag (1=yes)
`hispanic_serving`	int	yes	Hispanic-serving institution (1=yes)
`online_only`	int	yes	Online-only institution (1=yes)
`locale`	int	yes	NCES locale code
`size`	int	yes	Total enrollment (latest.student.size)
`pell_grant_rate`	double	yes	Share of students receiving Pell grants (latest.aid.pell_grant_rate)
`completion_rate_4yr`	double	yes	6-year completion rate at 150% time for 4yr institutions
`completion_rate_2yr`	double	yes	Completion rate for <4yr institutions
`retention_rate_fulltime`	double	yes	First-time full-time student retention rate (4yr)
`median_debt_completers`	double	yes	Median federal loan debt at completion (aid.median_debt.completers.overall)
`median_debt_noncompleters`	double	yes	Median federal loan debt for non-completers (aid.median_debt.noncompleters)
`mean_earnings_10yr`	int	yes	Mean earnings 10yr after entry for working non-enrolled students (note: mean, not median)
`median_earnings_8yr`	double	yes	Median earnings 8yr after entry (earnings.8_yrs_after_entry.median_earnings)
`median_family_income`	int	yes	Median family income of entering students
`default_rate_3yr`	double	yes	3-year student loan cohort default rate
`avg_net_price_public`	int	yes	Average net price for public institutions after aid
`avg_net_price_private`	int	yes	Average net price for private institutions after aid
`tuition_in_state`	int	yes	In-state tuition (cost.tuition.in_state)
`tuition_out_state`	int	yes	Out-of-state tuition (cost.tuition.out_of_state)

college_scorecard_programs · table¶

Dept of Ed College Scorecard program-level outcomes by CIP 4-digit code. One row per institution × program × credential level per year. Earnings by field of study — the most granular post-graduation outcome data. Joins to ipeds_completions via (unitid=unit_id, cipcode LIKE cip_code+'%'). PrivacySuppressed values are null.

Column	Type	Null	Description
`unit_id`	int	no	IPEDS unit ID — PK component; FK to ipeds_institutions.unitid
`ope6_id`	string	yes	OPE ID 6-digit
`year`	int	no	Data vintage year — PK component
`cip_code`	string	no	4-digit CIP code (e.g. "0199") — PK component
`cip_title`	string	yes	CIP field of study title
`credential_level`	int	no	Credential level code — PK component; 1=certificate <1yr, 2=certificate 1-2yr, 3=associate, 5=bachelor's, 7=master's, 17=doctoral
`credential_title`	string	yes	Credential level description
`ipeds_awards`	int	yes	IPEDS completions count for this program (counts.ipeds_awards1)
`median_earnings_1yr`	int	yes	Median earnings 1yr after completion (earnings.1_yr.overall_median_earnings)
`median_earnings_4yr`	int	yes	Median earnings 4yr after completion
`median_earnings_5yr`	int	yes	Median earnings 5yr after completion
`pell_median_earnings_1yr`	int	yes	Pell grant recipient median earnings 1yr after completion
`nonpell_median_earnings_1yr`	int	yes	Non-Pell recipient median earnings 1yr after completion

district_resources · view¶

District enrollment and staffing resource ratios. Joins CCD district directory to school-level lunch program aggregates for a poverty proxy. One row per district per year.