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Community-level data are available as CoDEC tables (see as_codec_tbl()) included with the codec package for R (see codec_read()).

The latest annual harmonized view across CoDEC tables is available in the interactive explorer:

Open the latest annual explorer

Variable-level metadata below now include direct links into the explorer when that field is part of codec_latest_annual.

American Community Survey Measures

About

Select population, socioeconomic, and housing measures derived from the 2024 5-yr U.S. Census American Community Survey (ACS) and were selected to cover three domains:

  • Population: number of kids, number of households (with kids), single-parent households, racial and ethnic composition, limited English speaking households
  • Socioeconomic: education, income, poverty, employment, health insurance, public income assistance
  • Housing: vacancy, age, value, tenure, rent to income ratio

Data

Types of ACS measures

Measures and their definitions are contained in make.R. Generally, each of the derived ACS measures are expressed in one of three ways:

  1. measures starting with n_ represent a number of something, such as n_household

  2. measures starting with prop_ represent a proportion of some total, such as prop_poverty

  3. measures starting with median_ represent a median of a number in a population, such as median_income

Missing Data

Additionally, data summaries may be suppressed by the census bureau.

Source Rights and Licenses

ACS estimates are produced by the U.S. Census Bureau. As U.S. federal government data, these source data can be redistributed and used to create derived CoDEC measures with Census source attribution and the ACS release year retained.

Metadata

This CoDEC table has 226 rows and 24 columns
column name class example explore
n_households integer 1342 open
census_tract_id_2020 character 39061022102
n_households_children integer 363 open
n_housing_units integer 2696 open
prop_poverty numeric 0.1272 open
prop_recieved_public_assistance_income numeric 0.1615 open
prop_family_households_with_single_householder numeric 0.6432 open
prop_employment_among_civilian_workforce numeric 0.8091 open
prop_housing_units_occupied_by_renters numeric 0.2789 open
prop_median_rent_to_income_ratio_among_renters numeric 29 open
prop_housing_units_vacant numeric 0.0185 open
prop_white_and_not_hispanic_or_latino numeric 0.7164 open
prop_black_and_not_hispanic_or_latino numeric 0.5478 open
prop_white_and_hispanic_or_latino numeric 0 open
prop_black_and_hispanic_or_latino numeric 0 open
n_persons_under_18 integer 802 open
prop_health_insurance numeric 0.8784 open
prop_rent_burdened numeric 0.5286 open
prop_housing_conditions numeric 0.2287 open
prop_built_prior_1980 numeric 0.3562 open
prop_limited_english_speaking numeric 0 open
prop_adults_hs_edu numeric 0.9824 open
year integer 2024
median_home_value integer 166300 open

Download

In R:

codec::codec_read("acs_measures")

Manually:

Download csv ⬇️

 

 

Crime

About

Census tract-level measures of crime incidents (including property crimes, violent crimes, other crimes, gunshots, and reported shootings) in Hamilton County, Ohio.

Tract-level measures are derived from the data packages stored in the xx_address repository, including crime_incidents-v0.1.2, shotspotter-v0.1.2, and reported_shootings-v0.1.0. View the metadata for each of these data packages for more information about their sources.

Data

Jittered (within the same block) latitude and longitude corresponding to the location of each reported crime are available from each data source. Crimes are aggregated to the tract level by summing the number of crimes for each tract. For higher resolution crime data, see the xx_address repository.

Because of how the data is available, values will be missing (NA) if either (1) there were zero instances in a tract-year-month or (2) it is outside the spatial or temporal extent for the respective data source. In some cases, it may be appropriate to impute zero instances in place of missing counts; for example, if it is clear that the tract was measured the month before and after in the same year. More specifically:

  • crime_incidents and reported_shootings are geographically limited to the City of Cincinnati
  • shotspotter is limited to specific time periods for different target neighborhoods

Metadata

This CoDEC table has 21,696 rows and 8 columns
column name class example explore
census_tract_id_2020 character 39061020811
year integer 2017
month integer 7
n_crime_incidents_property integer 7
n_crime_incidents_violent integer 1
n_crime_incidents_other integer 2
n_shots_fired integer 10
n_reported_shootings integer 1

Download

In R:

codec::codec_read("crime")

Manually:

Download csv ⬇️

 

 

Average Drive Time to Cincinnati Children’s

About

A census tract-level measure of drive time to Cincinnati Children’s Hospital Medical Center derived using 6-minute interval drive time isochrones obtained from openroute service.

Data

Each tract-level drive time is an area-weighted average of intersecting 6-minute interval drive time isochrones calculated for the packaged 2020 census tract geographies.

Source Rights and Licenses

Drive-time isochrones are derived from openrouteservice outputs. The openrouteservice Terms of Service state that API results are licensed under CC-BY-4.0. Source terms: openrouteservice Terms of Service. CoDEC can redistribute the derived tract-level measure when attribution to openrouteservice/HeiGIT and OpenStreetMap contributors is retained.

Metadata

This CoDEC table has 226 rows and 3 columns
column name class example explore
census_tract_id_2020 character 39061026800
drive_time_avg numeric 15.8 open
year integer 2024

Download

In R:

codec::codec_read("drivetime")

Manually:

Download csv ⬇️

 

 

Environmental Justice Index

About

The Environmental Justice Index uses data from the U.S. Census Bureau, the U.S. Environmental Protection Agency, the U.S. Mine Safety and Health Administration, and the U.S. Centers for Disease Control and Prevention to rank the cumulative impacts of environmental injustice on health for every census tract. … The EJI ranks each tract on 36 environmental, social, and health factors and groups them into three overarching modules and ten different domains.

The ATSDR’s Environmental Justice Index (EJI) was most recently released in 2024, but utilizes data from several older sources. Note that although the EJI data has a year of 2024 in the CoDEC data package, fields in the EJI are from different sources that are each actually older. Find the full documentation of the EJI in PDF form here: https://www.atsdr.cdc.gov/place-health/media/pdfs/2024/10/EJI_2024_Technical_Documentation.pdf

Data

  • Data download from https://www.atsdr.cdc.gov/placeandhealth/eji/eji-data-download.html as a geodatabase
  • Data fields representing “estimates” (i.e., not “percentile” or “summed ranks”) selected if not available elsewhere (e.g., not American Community Survey estimates)
  • Field names were renamed to be longer and more descriptive
  • Although this is the 2022 release, 2010 vintage census tract geographies and identifiers are used in the EJI data

Source Rights and Licenses

The Environmental Justice Index is produced by CDC/ATSDR. As a U.S. federal government product, the EJI can be redistributed and used to create derived CoDEC measures; because the index incorporates several federal and third-party source systems, CoDEC retains the EJI release year, documentation URL, access date, and source attribution.

Metadata

This CoDEC table has 226 rows and 15 columns
column name class example explore
census_tract_id_2020 character 39061026600
prcnt_area_within_1mi_epa_npl_site numeric 0 open
prcnt_area_within_1mi_epa_tri_site numeric 82.7213 open
prcnt_area_within_1m_epa_tsd_site numeric 100 open
prcnt_area_within_1mi_epa_rmp_site numeric 3.1943 open
prcnt_area_within_1mi_coal_mine integer 0 open
prcnt_area_within_1mi_lead_mine integer 0 open
prcnt_area_within_1_mi_greenspace numeric 100 open
prcnt_homes_built_before_1980 numeric 57.3 open
walkability_index_epa numeric 7.2 open
prcnt_area_within_1mi_railroad numeric 100 open
prcnt_area_within_1mi_high_volume_road numeric 0 open
prcnt_area_within_1mi_airport numeric 0 open
prcnt_area_huc12_watershed numeric 0.321 open
year integer 2024

Download

In R:

codec::codec_read("environmental_justice_index")

Manually:

Download csv ⬇️

 

 

Landcover, Built Environment, and Greenness

About

The National Landcover Database (NLCD) is an annual product that summarizes fraction imperviousness (fractional surface area covered with artificial substrate or structures) at a 30 m grid. The fraction imperviousness is averaged through spatial intersection with the 2020 census tract boundaries.

Data

Cloud-optimized GeoTIFF files are hosted on Harvard’s Dataverse (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/KXETFC). These files were downloaded from the Annual NLCD Product Suite and converted from GeoTIFF to cloud-optimized GeoTIFF (COG) using gdal_translate.

Source Rights and Licenses

Annual NLCD products are produced by USGS. As U.S. federal government data, NLCD products can be redistributed and used to create derived CoDEC measures with USGS credit; CoDEC also preserves the Harvard Dataverse DOI, access URL, and access date for the COG mirror used here.

Metadata

This CoDEC table has 904 rows and 3 columns
column name class example explore
census_tract_id_2020 character 39061004603
year integer 2022
mean_pct_impervious numeric 63.0404 open

Download

In R:

codec::codec_read("landcover")

Manually:

Download csv ⬇️

 

 

Parcel Characteristics

About

Census tract-level measures of parcel characteristics for all residential parcles in Hamilton County, Ohio. Tract-level measures are derived from the data packages stored in the parcel repository. Version 0.1.0 of the parcel CoDEC data resource harmonizes cagis_parcels-v1.1.1 and auditor_online_parcels-v0.2.1. View the metadata for each of these data packages for more information about their sources.

Data

Parcel-level measures were aggregated to the tract level:

  • median: market_total_value, acreage, year_built, and number of rooms
  • fraction of parcels: by land use type, by homestead flag

Parcel land use types were grouped into more general categories:

  • apartments: apartment, 4-19 units, apartment, 20-39 units, apartment, 40+ units, office / apartment over
  • assisted housing: metropolitan housing authority, lihtc res
  • condominiums: condominium unit, condo or pud garage
  • single family homes: single family dwelling
  • two to three family homes: two family dwelling, three family dwelling
  • other

Metadata

This CoDEC table has 222 rows and 17 columns
column name class example explore
census_tract_id_2010 character 39061024001
fraction_apartment numeric 0.01 open
fraction_assisted_housing numeric 0.03 open
market_total_value integer 67380 open
acreage numeric 0.117 open
year_built numeric 1890 open
n_total_rooms integer 6 open
n_bedrooms numeric 3 open
n_full_bathrooms integer 1 open
n_half_bathrooms integer 0 open
online_market_total_value integer 213245 open
year integer 2024
fraction_condominium numeric 0.05 open
fraction_single_family_dwelling numeric 0.8 open
fraction_two_to_three_family_dwelling numeric 0.06 open
fraction_homestead numeric 0.2 open
fraction_other numeric 0 open

Download

In R:

codec::codec_read("parcel")

Manually:

Download csv ⬇️

 

 

Property Code Enforcements

About

Tract-level measures are derived from the property_code_enforcements-v1.0.1 data package stored in the parcel repository.

Data

The census tract-level number of property code enforcements (n_property_code_enforcements) is calculated by intersecting the jittered coordinates of the enforcements with the 2020 census tract boundaries and totaling them per year (2017 - present).

Metadata

This CoDEC table has 2,034 rows and 3 columns
column name class example explore
census_tract_id_2020 character 39061026800
year integer 2019
n_property_code_enforcements integer 0 open

Download

In R:

codec::codec_read("property_code_enforcements")

Manually:

Download csv ⬇️

 

 

Average Annual Vehicle-Meters Driven

About

Traffic is measured in AADTM or Annual Average Daily Traffic Meters, which is the average number of total meters driven by all vehicles per day when grouped into classes (trucks/buses, tractor/trailer, passenger).

For more details about the HPMS, see:

Data

Data is downloaded from the 2020 Highway Performance Monitoring System (HPMS) geodatabase hosted by ESRI using the {appc} package for R. Only roads with F_SYSTEM classification of 1 (“interstate”) or 2 (“principal arterial - other freeways and expressways”) are used. Passenger vehicles (FHWA 1-3) are calculated as the total minus FHWA class 4-7 (single unit) and 8-13 (combo).

For each 2020 census tract geography, sum the class-specific AADTM for all intersecting roads, weighted by their intersecting lengths.

Source Rights and Licenses

HPMS data are produced by FHWA / USDOT. As U.S. federal government data, HPMS can be redistributed and used to create derived CoDEC measures with HPMS source attribution, publication year, access URL, and access date retained.

Metadata

This CoDEC table has 226 rows and 5 columns
column name class example explore
census_tract_id_2020 character 39061026800
aadtm_trucks_buses numeric 16711617.9611 open
aadtm_tractor_trailer numeric 35998046.0958 open
aadtm_passenger numeric 0 open
year integer 2020

Download

In R:

codec::codec_read("traffic")

Manually:

Download csv ⬇️