This interactive map uses almost 300 data variables at the zip code geography for metro Atlanta. The data includes the U.S. Census Bureau 2010 Decennial Census and the latest American Community Survey (2011-2015), business and establishment data (from the Census Zip Code Business Patterns), Earned Income Tax Credit usage (from Brookings and IRS) and data from Zillow about home sales prices and negative equity. The map uses the Weave interactive platform, which allows the user to select data variables and customize related data visualizations (charts/graphs).

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.

For a deep dive into the data model including every specific metric, see the ACS 2016-2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

s

Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed

Suffixes:

_e20

Estimate from 2016-20 ACS

_m20

Margin of Error from 2016-20 ACS

_e10

2006-10 ACS, re-estimated to 2020 geography

_m10

Margin of Error from 2006-10 ACS, re-estimated to 2020 geography

_e10_20

Change, 2010-20 (holding constant at 2020 geography)

Geographies

AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)

ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)

Census Tracts (statewide)

CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)

City (statewide)

City of Atlanta Council Districts (City of Atlanta)

City of Atlanta Neighborhood Planning Unit (City of Atlanta)

City of Atlanta Neighborhood Planning Unit STV (subarea of City of Atlanta)

City of Atlanta Neighborhood Statistical Areas (City of Atlanta)

County (statewide)

Georgia House (statewide)

Georgia Senate (statewide)

MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)

Regional Commissions (statewide)

State of Georgia (statewide)

Superdistrict (ARC region)

US Congress (statewide)

UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)

WFF = Westside Future Fund (subarea of City of Atlanta)

ZIP Code Tabulation Areas (statewide)

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2016-2020). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Source: U.S. Census Bureau, Atlanta Regional Commission Date: 2016-2020 Data License: Creative Commons Attribution 4.0 International (CC by 4.0)

Link to the manifest: https://opendata.atlantaregional.com/documents/GARC::acs-2020-data-manifest/about

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show numbers and percentages for occupation, household income, and commuting pattern by race and by Zip Code Tabulation Area in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

Attributes and definitions available below under "Attributes" section and in Infrastructure Manifest (due to text box constraints, attributes cannot be displayed here).

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from American Community Survey 5-year estimates for 2011-2015 to show housing affordability data (housing costs relative to income) by zip code in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. ACS data presented here represent combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2011-2015). Therefore, these data do not represent any one specific point in time or even one specific year. For further explanation of ACS estimates and methodology, click here.

Attributes:

ZIP = Zip code (text)

ZIP_dbl = Zip code (numeric)

Total_Population_2010 = Total Population, 2010 Census

Total_Population_2011_2015_ACS = Total Population, 2011-2015 American Community Survey (ACS)

HousUnits_MonthOwnerCosts_toInc = #, Housing units for which Selected Monthly Owner Costs as % of income are computed

Sel_Mo_Own_Costs_30pct_of_Incom = #, Selected Monthly Owner Costs (SMOCAPI) are 30% or more of household income

Pct_Sel_Mo_Own_Costs_30pct_Inc = %, Selected Monthly Owner Costs (SMOCAPI) are 30% or more of household income

HousUnits_Compute_RentPctIncome = #, Housing units for which Gross rent as a percentage of income is computed

Rent_Pct_of_Inc_More30Pct = #, Gross rent as a percentage of household income (GRAPI) is 30% or more

PctRent_PctIncome_More30Pct = %, Gross rent as a percentage of household income (GRAPI) is 30% or more

HousUnits_OwnRent_Compute = #, Housing units for which SMOCAPI or GRAPI are computed

HousCosts_Units_30pctMore_Inc = #, Housing costs (GRAPI or SMOCAPI) are 30% or more of household income

PctHousCost_30pctMore_Income = %, Housing costs (GRAPI or SMOCAPI) are 30% or more of household income

last_edited_date = Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2011-2015

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau.For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.Naming conventions:Prefixes: None Countp Percentr Ratem Mediana Mean (average)t Aggregate (total)ch Change in absolute terms (value in t2 - value in t1)pch Percent change ((value in t2 - value in t1) / value in t1)chp Change in percent (percent in t2 - percent in t1)s Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed Suffixes: _e19 Estimate from 2014-19 ACS_m19 Margin of Error from 2014-19 ACS_00_v19 Decennial 2000, re-estimated to 2019 geography_00_19 Change, 2000-19_e10_v19 2006-10 ACS, re-estimated to 2019 geography_m10_v19 Margin of Error from 2006-10 ACS, re-estimated to 2019 geography_e10_19 Change, 2010-19The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2015-2019). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2015-2019Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the manifest: https://www.arcgis.com/sharing/rest/content/items/3d489c725bb24f52a987b302147c46ee/data

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2011-2015, to show various demographic data by zip code in the Atlanta region (including the following categories: total population, age, race/ethnicity, household composition, grandparents, school enrollment, educational attainment, veteran status, disability, foreign born status, linguistic isolation, unemployment, commuting mode, occupation, income, health insurance, poverty, housing characteristics, vehicle availability, housing values, and housing affordability).The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. The Census Bureau also calculates a corresponding margin of error (MOE) for ACS measures (although margins of error are not included in this dataset).The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2011-2015). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.For further explanation of ACS estimates and margin of error, refer to Census Bureau documentation.- - - - - -Base Attributes:ZIP = Zip code (text)ZIP_dbl = Zip code (numeric)Total_Population_2010= Total Population, 2010 CensusTotal_Population_2011_2015_ACS= Total Population, 2011-2015 American Community Survey (ACS)- - - - - -Attributes from ACS:Workers_16_years_and_over= Number, Workers, 16 years and overCar_Truck_or_Van_drove_alone= Number, Car, truck, or van – drove alonePct_Car_Truck_Van_drove_alone= Percent, Car, truck, or van – drove aloneCar_truck_or_van_carpooled= Number, Car, truck, or van – carpooledPct_Car_Truck_Van_carpooled= Percent, Car, truck, or van – carpooledPublic_Transport_excluding_Taxi= Number, Public transportation (excluding taxicab)Pct_Public_Transp_exclude_Taxi= Percent, Public transportation (excluding taxicab)Worked_at_home= Number, Worked at homePct_Worked_at_home= Percent, Worked at homeMean_Travel_Time_to_Work_min= Mean travel time to work (minutes)- - - - - -Civilian_nonInstitutional_Pop= Total Civilian Noninstitutionalized PopulationCiv_nonInstitution_Pop_wDisabil= #, Civilian Noninstitutionalized Population With a disabilityPct_Civ_nonInstitut_Pop_wDisab= %, Civilian Noninstitutionalized Population With a disabilityCiv_nonInstitut_Pop_under_18yrs= #, Civilian Noninstitutionalized Population Under 18 yearsCiv_nonInst_under18_wDisab= #, Civilian Noninstitutionalized Under 18 years With a disabilityPct_Civ_nonInst_under18_wDisab= %, Civilian Noninstitutionalized Under 18 years With a disabilityCiv_nonInst_Pop_18_to_64= #, Civilian Noninstitutionalized Population 18 to 64 yearsCiv_nonInst_18_to_64_wDisab= #, Civilian Noninstitutionalized 18 to 64 years With a disabilityPct_Civ_nonInst_18to64_wDisab= %, Civilian Noninstitutionalized 18 to 64 years With a disabilityCiv_nonInst_Pop_65years_up= #, Civilian Noninstitutionalized Population 65 years and overCiv_nonInst_65up_wDisab= #, Civilian Noninstitutionalized 65 years and over With a disabilityPct_Civ_nonInst_65up_wDisab= %, Civilian Noninstitutionalized 65 years and over With a disability- - - - - -Population_25_years_and_over= #, Population 25 years and overLess_than_HS_or_GED= #, Less than HS or GEDPercent_Less_than_HS_or_GED= %, Less than HS or GEDBA_or_Higher= #, BA or HigherPercent_BA_or_Higher= %, BA or Higher- - - - - -US_Native= #, U.S. NativePercent_US_Native= %, U.S. NativeUSnative_Born_in_US= #, U.S. Native, Born in the United StatesPct_USnative_Born_US= %, U.S. Native, Born in the United StatesUSnative_Born_State_Resid= #, U.S. Native, Born in State of ResidencePct_USnative_Born_State_Resid= %, U.S. Native, Born in State of ResidenceUS_Native_Born_Diff_State= #, U.S. Native, Born in Different StatePct_US_Natv_Born_inDiff_State= %, U.S. Native, Born in Different StateForeign_Born= #, Foreign BornPercent_Foreign_Born= %, Foreign BornForBorn_Nat_UScitizen= #, Foreign Born, Naturalized U.S. CitizenPct_ForBorn_Nat_UScitizen= %, Foreign Born, Naturalized U.S. CitizenForeignBorn_notUS_Citizen= #, Foreign Born, Not a U.S. CitizenPct_ForBorn_notUS_Citizen= %, Foreign Born, Not a U.S. Citizen- - - - - -GParents_Liv_wOwn_GChild_und18= #, Grandparents living with own grandchildren under 18 yearsGParents_RespFor_Gchildren= #, Grandparents Responsible for grandchildrenPct_GPar_RespFor_Gchildren= %, Grandparents Responsible for grandchildren- - - - - -Pop_wHealth_Insurance= #, Civilian noninstitutionalized population with health insurance coveragePct_Pop_wHealth_Ins= %, Civilian noninstitutionalized population with health insurance coveragePop_wPriv_Health_Ins= #, Civilian noninstitutionalized population with private health insurancePct_Pop_wPriv_Health_Ins= %, Civilian noninstitutionalized population with private health insurancePopulation_with_public_coverage= #, Civilian noninstitutionalized population with public coveragePct_Pop_with_public_coverage= %, Civilian noninstitutionalized population with public coveragePop_wNo_Health_Ins= #, Civilian noninstitutionalized population with no health insurance coveragePct_Pop_wNo_Health_Ins= %, Civilian noninstitutionalized population with no health insurance coveragePop_u18_wNo_Health_Ins= #, Civilian Noninstitutionalized Population Under 18 years with no health insurancePct_Pop_u18_wNo_Health_Ins= %, Civilian Noninstitutionalized Population Under 18 years with no health insurancePop_18to64_Employed= #, Civilian noninstitutionalized ages 18 to 64, employedPop_18to64_Empl_wNo_Health_Ins= #, Civilian noninstitutionalized ages 18 to 64, employed with no health insurancePct_Pop_18to64_Emp_wNo_Hlth_Ins= %, Civilian noninstitutionalized ages 18 to 64, employed with no health insurancePop_18to64_Unemployed= #, Civilian noninstitutionalized ages 18 to 64, unemployedPop_18to64_Unemp_wNo_Health_Ins= #, Civilian noninstitutionalized ages 18 to 64, unemployed with no health insurancePct_Pop_18to64_Unemp_No_HlthIns= %, Civilian noninstitutionalized ages 18 to 64, unemployed with no health insurancePop_18to64_Not_in_Labor_Force= #, Civilian noninstitutionalized ages 18 to 64, not in labor forcePop_18to64_Not_LabFor_NoHlthIns= #, Civilian noninstitutionalized ages 18 to 64, not in labor force with no health insurancePctPop_18to64_NotLFor_NoHlthIns= %, Civilian noninstitutionalized ages 18 to 64, not in labor force with no health insurance- - - - - -HousUnits_MonthOwnerCosts_toInc= #, Housing units for which Selected Monthly Owner Costs as % of income are computedSel_Mo_Own_Costs_30pct_of_Incom= #, Selected Monthly Owner Costs (SMOCAPI) are 30% or more of household incomePct_Sel_Mo_Own_Costs_30pct_Inc= %, Selected Monthly Owner Costs (SMOCAPI) are 30% or more of household incomeHousUnits_Compute_RentPctIncome= #, Housing units for which Gross rent as a percentage of income is computedRent_Pct_of_Inc_More30Pct= #, Gross rent as a percentage of household income (GRAPI) is 30% or morePctRent_PctIncome_More30Pct= %, Gross rent as a percentage of household income (GRAPI) is 30% or moreHousUnits_OwnRent_Compute= #, Housing units for which SMOCAPI or GRAPI are computedHousCosts_Units_30pctMore_Inc= #, Housing costs (GRAPI or SMOCAPI) are 30% or more of household incomePctHousCost_30pctMore_Income= %, Housing costs (GRAPI or SMOCAPI) are 30% or more of household income- - - - - -Total_housing_units= Total housing unitsOccupied_housing_units= #, Occupied housing unitsPercent_Occupied_housing_units= %, Occupied housing unitsVacant_housing_units= #, Vacant housing unitsPercent_Vacant_housing_units= %, Vacant housing unitsHomeowner_vacancy_rate= Homeowner vacancy rateRental_vacancy_rate= Rental vacancy rateOne_unit_detatched_housing_unit= #, 1-unit detached housing unitsPercent_1Unit_Detached= %, 1-unit detached housing unitsHousing_units_built_since_2000= #, Housing units built since 2000Pct_Units_Built_Since_2000= %, Housing units built since 2000Units_Built_1980_to_1999= #, Housing units built 1980 to 1999Pct_Units_Built_1980_to_1999= %, Housing units built 1980 to 1999Units_Built_1979_or_Earlier= #, Housing units built 1979 or earlierPct_Units_Built_1979_or_Earlier= %, Housing units built 1979 or earlierOwner_occupied_housing_units= Housing Tenure: #, Owner occupied housing unitsPct_Owner_Occ_HousUnits= Housing Tenure: %, Owner occupied housing unitsRenter_occupied_housing_units= Housing Tenure: #, Renter occupied housing unitsPct_Renter_Occ_Units= Housing Tenure: %, Renter occupied housing units- - - - - -OwnOcc_units_valued_less_100k= #, Owner occupied housing units valued less than $100,000Pct_OwnOcc_units_val_less_100k= %, Owner occupied housing units valued less than $100,000OwnOcc_units_valued_100k_300k= #, Owner occupied housing units valued $100,000-$299,999Pct_OwnOcc_units_val_100k_300k= %, Owner occupied housing units valued $100,000-$299,999OwnOcc_units_valued_300k_more= #, Owner occupied housing units valued $300,000 or morePct_OwnOcc_units_val_300k_more= %, Owner occupied housing units valued $300,000 or moreMedian_value_own_occ_units= Median value, owner occupied housing units- - - - - -Income_Total_households = Income: Total householdsHousehold_inc_less_35k= #, Household income less than $35,000Pct_Household_inc_less_35k= %, Household income less than $35,000Household_inc_35k_75k= #, Household income