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In October 2015, Mayor Garcetti released Executive Directive 13, Support for Affordable Housing (ED 13). ED 13 is a “Back to Basics” operational directive that helps streamline the development of critical new housing developments that address our housing shortage.
This dataset tracks the City's progress towards the goals outlined in the directive: (1) Permitting 100,000 new units from the start of Mayor Garcetti's administration through the end of fiscal year 2021, and (2) Building or preserving 15,000 affordable housing units for low-income households in this same time period.
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
List of Properties owned by the Housing Authority of the City of Los Angeles. Updated January 2015.
This is a dataset hosted by the city of Los Angeles. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore Los Angeles's Data using Kaggle and all of the data sources available through the city of Los Angeles organization page!
This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.
Cover photo by Christiana Rivers on Unsplash
Unsplash Images are distributed under a unique Unsplash License.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset presents the median household income across different racial categories in Los Angeles County. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Los Angeles County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 35.43% of the total residents in Los Angeles County. Notably, the median household income for White households is $101,816. Interestingly, despite the White population being the most populous, it is worth noting that Native Hawaiian and Other Pacific Islander households actually reports the highest median household income, with a median income of $107,300. This reveals that, while Whites may be the most numerous in Los Angeles County, Native Hawaiian and Other Pacific Islander households experience greater economic prosperity in terms of median household income.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Los Angeles County median household income by race. You can refer the same here
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License information was derived automatically
Locations of offices associated with the Los Angeles Housing and Community Investment Department which provide services to city residents.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
"Due to the size of this dataset, both Shapefile and Spreadsheet download options will not work as expected. The File Geodatabase is an alternative option for this data download"SCAG has developed its regional geospatial dataset of land use information at the parcel-level (approximately five million parcels) for 197 local jurisdictions in its region. The regional land use dataset is developed (1) to aid in SCAG’s regional transportation planning, scenario planning and growth forecasting, (2) facilitate policy discussion on various planning issues, and (3) enhance information database to better serve SCAG member jurisdictions, research institutes, universities, developers, general public, etc. This is SCAG's 2016 regional land use dataset developed for the Final Connect SoCal, the 2020-2045 Regional Transportation Plan/Sustainable Communities Strategy (RTP/SCS), including general plan land use, specific plan land use, zoning code and existing land use. Please note this data was reviewed by local jurisdictions and reflects each jurisdiction's input received during the Connect SoCal Local Input and Envisioning Process.Note: This dataset is intended for planning purposes only, and SCAG shall incur no responsibility or liability as to the completeness, currentness, or accuracy of this information. SCAG assumes no responsibility arising from use of this information by individuals, businesses, or other public entities. The information is provided with no warranty of any kind, expressed or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose. Users should consult with each local jurisdiction directly to obtain the official land use information.Data DictionaryField NameData TypeField DescriptionOBJECTIDObject IDInternal feature numberShapeGeometryType of geometrySCAGUID16Text2016 SCAG unique identification numberSCAGUID12Text2012 SCAG unique identification numberAPNTextAssessor’s parcel numberCOUNTYTextCounty nameCOUNTY_IDDoubleCounty FIPS codeCITYTextCity nameCITY_IDDoubleCity FIPS codeACRESDoubleAcreage informationYEARDoubleDataset yearCITY_GP_COText2016 Jurisdiction’s general plan land use designationSCAG_GP_COText2016 SCAG general plan land use codeDENSITYDoubleAverage density of residential/housing development (dwelling unit per acre) permitted based on jurisdiction’s general planLOWDoubleMinimum density of residential/housing development permitted (dwelling unit per acre) based on jurisdiction’s general planHIGHDoubleMaximum density of residential/housing development permitted (dwelling unit per acre) based on jurisdiction’s general planYEAR_ADOPTDateYear when jurisdiction adopted/last updated current general plan land use elementGP12_CITYText2012 jurisdiction’s general plan land use designationGP12_SCAGText2012 SCAG general plan land use codeSP_NAMETextSpecific plan nameCITY_SP_COText2016 Jurisdiction’s specific plan land use designationSCAG_SP_COText2016 SCAG specific plan land use codeDENSITY_SPDoubleAverage density of residential/housing development (dwelling unit per acre) permitted based on jurisdiction’s specific planLOW_SPDoubleMinimum density of residential/housing development permitted (dwelling unit per acre) based on jurisdiction’s specific planHIGH_SPDoubleMaximum density of residential/housing development permitted (dwelling unit per acre) based on jurisdiction’s specific planYR_AD_SPDateYear when jurisdiction adopted/last updated current specific planSP_INDEXShort IntegerSpecific plan index ('0' = outside specific plan area; '1' = inside specific plan area)CITY_ZN_COText2016 Jurisdiction’s zoning codeSCAG_ZN_COText2016 SCAG zoning codeZN12_CITYText2012 jurisdiction’s zoning codeLU16Text2016 SCAG existing land use codeLU12Text2012 SCAG existing land use codeNOTESTextAdditional informationShape_LengthDoubleLength of feature in internal unitsShape_AreaDoubleArea of feature in internal units squared2016 SCAG Land Use CodesLegendLand Use DescriptionSingle Family Residential1110 Single Family Residential1111 High Density Single Family Residential (9 or more DUs/ac)1112 Medium Density Single Family Residential (3-8 DUs/ac)1113 Low Density Single Family Residential (2 or less DUs/ac)Multi-Family Residential1120 Multi-Family Residential1121 Mixed Multi-Family Residential1122 Duplexes, Triplexes and 2- or 3-Unit Condominiums and Townhouses1123 Low-Rise Apartments, Condominiums, and Townhouses1124 Medium-Rise Apartments and Condominiums1125 High-Rise Apartments and CondominiumsMobile Homes and Trailer Parks1130 Mobile Homes and Trailer Parks1131 Trailer Parks and Mobile Home Courts, High-Density1132 Mobile Home Courts and Subdivisions, Low-DensityMixed Residential1140 Mixed Residential1100 ResidentialRural Residential1150 Rural ResidentialGeneral Office1210 General Office Use1211 Low- and Medium-Rise Major Office Use1212 High-Rise Major Office Use1213 SkyscrapersCommercial and Services1200 Commercial and Services1220 Retail Stores and Commercial Services1221 Regional Shopping Center1222 Retail Centers (Non-Strip With Contiguous Interconnected Off-Street Parking)1223 Retail Strip Development1230 Other Commercial1231 Commercial Storage1232 Commercial Recreation1233 Hotels and MotelsFacilities1240 Public Facilities1241 Government Offices1242 Police and Sheriff Stations1243 Fire Stations1244 Major Medical Health Care Facilities1245 Religious Facilities1246 Other Public Facilities1247 Public Parking Facilities1250 Special Use Facilities1251 Correctional Facilities1252 Special Care Facilities1253 Other Special Use FacilitiesEducation1260 Educational Institutions1261 Pre-Schools/Day Care Centers1262 Elementary Schools1263 Junior or Intermediate High Schools1264 Senior High Schools1265 Colleges and Universities1266 Trade Schools and Professional Training FacilitiesMilitary Installations1270 Military Installations1271 Base (Built-up Area)1272 Vacant Area1273 Air Field1274 Former Base (Built-up Area)1275 Former Base Vacant Area1276 Former Base Air FieldIndustrial1300 Industrial1310 Light Industrial1311 Manufacturing, Assembly, and Industrial Services1312 Motion Picture and Television Studio Lots1313 Packing Houses and Grain Elevators1314 Research and Development1320 Heavy Industrial1321 Manufacturing1322 Petroleum Refining and Processing1323 Open Storage1324 Major Metal Processing1325 Chemical Processing1330 Extraction1331 Mineral Extraction - Other Than Oil and Gas1332 Mineral Extraction - Oil and Gas1340 Wholesaling and WarehousingTransportation, Communications, and Utilities1400 Transportation, Communications, and Utilities1410 Transportation1411 Airports1412 Railroads1413 Freeways and Major Roads1414 Park-and-Ride Lots1415 Bus Terminals and Yards1416 Truck Terminals1417 Harbor Facilities1418 Navigation Aids1420 Communication Facilities1430 Utility Facilities1431 Electrical Power Facilities1432 Solid Waste Disposal Facilities1433 Liquid Waste Disposal Facilities1434 Water Storage Facilities1435 Natural Gas and Petroleum Facilities1436 Water Transfer Facilities1437 Improved Flood Waterways and Structures1438 Mixed Utilities1440 Maintenance Yards1441 Bus Yards1442 Rail Yards1450 Mixed Transportation1460 Mixed Transportation and UtilityMixed Commercial and Industrial1500 Mixed Commercial and IndustrialMixed Residential and Commercial1600 Mixed Residential and Commercial1610 Residential-Oriented Residential/Commercial Mixed Use1620 Commercial-Oriented Residential/Commercial Mixed UseOpen Space and Recreation1800 Open Space and Recreation1810 Golf Courses1820 Local Parks and Recreation1830 Regional Parks and Recreation1840 Cemeteries1850 Wildlife Preserves and Sanctuaries1860 Specimen Gardens and Arboreta1870 Beach Parks1880 Other Open Space and Recreation1890 Off-Street TrailsAgriculture2000 Agriculture2100 Cropland and Improved Pasture Land2110 Irrigated Cropland and Improved Pasture Land2120 Non-Irrigated Cropland and Improved Pasture Land2200 Orchards and Vineyards2300 Nurseries2400 Dairy, Intensive Livestock, and Associated Facilities2500 Poultry Operations2600 Other Agriculture2700 Horse RanchesVacant3000 Vacant3100 Vacant Undifferentiated3200 Abandoned Orchards and Vineyards3300 Vacant With Limited Improvements3400 Beaches (Vacant)1900 Urban VacantWater4000 Water4100 Water, Undifferentiated4200 Harbor Water Facilities4300 Marina Water Facilities4400 Water Within a Military Installation4500 Area of Inundation (High Water)Specific Plan7777 Specific PlanUnder Construction1700 Under ConstructionUndevelopable or Protected Land8888 Undevelopable or Protected LandUnknown9999 Unknown
Severe housing burden is defined as spending 50% or more of monthly household income on housing. A small number of households without housing cost or income data were excluded from analyses.Given the high cost of housing in Los Angeles County, many residents spend a sizable portion of their incomes on housing every month. Severe housing burden disproportionately affects low-income individuals, renters, and communities of color. Severe housing burden can negatively impact health by forcing individuals and families into low quality or unsafe housing, by causing significant stress, and by limiting the amount of money people have available to spend on other life necessities, such as food or healthcare. It is also an important risk factor for homelessness.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.
Housing affordability is a major concern for many Los Angeles County residents. Housing constitutes the single largest monthly expense for most people. Renters are more susceptible than homeowners to high housing costs, especially if they live in a community without rent control or other tenant protection policies. Compared to homeowners, renters are also more likely to experience housing burden or housing instability and have a higher risk for homelessness.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.
This dataset provides information about the number of properties, residents, and average property values for Garden Homes Avenue cross streets in Los Angeles, CA.
Housing affordability is a major concern for many Los Angeles County residents. Housing constitutes the single largest monthly expense for most people. Among homeowners, their homes are often their largest financial assets. Home ownership can also offer many benefits, including the opportunity to increase financial security and build wealth.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.
According to U.S. Department of Housing and Urban Development's definition, homelessness includes individuals and families who lack a fixed, regular, and adequate nighttime residence. A homeless count provides a "snapshot in time" to quantify the size of the homeless population at a specific point during the year. Regardless of how successful outreach efforts are, an undercount of people experiencing homelessness is possible. Counts includes persons experiencing unsheltered and sheltered homelessness. Greater Los Angeles Homeless Count occurred in the nights of February 22, 23 and 24, 2022. Glendale's count occurred in the morning and evening of February 25, 2022. Long Beach's count occurred in the early morning of February 24, 2022. Pasadena's count occurred in the evening of February 22, 2022 and morning of February 23, 2022. Data not available for Los Angeles City neighborhoods and unincorporated Los Angeles County; LAHSA does not recommend aggregating census tract-level data to calculate numbers for other geographic levels.Housing affordability is a major concern for many Los Angeles County residents. Housing burden can increase the risk for homelessness. Individuals experiencing homelessness experience disproportionately higher rates of certain health conditions, such as tuberculosis, HIV infection, alcohol and drug abuse, and mental illness. Barriers to accessing care and limited access to resources contribute greatly to these observed disparities.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.
This EnviroAtlas dataset describes the block group population and the percentage of the block group population that has potential views of water bodies. A potential view of water is defined as having a body of water that is greater than 300m2 within 50m of a residential location. The window views are considered "potential" because the procedure does not account for presence or directionality of windows in one's home. The residential locations are defined using the EnviroAtlas Dasymetric (2011/October 2015) map. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of Los Angeles by race. It includes the distribution of the Non-Hispanic population of Los Angeles across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Los Angeles across relevant racial categories.
Key observations
Of the Non-Hispanic population in Los Angeles, the largest racial group is White alone with a population of 1.09 million (53.68% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Los Angeles Population by Race & Ethnicity. You can refer the same here
Esri’s Housing Affordability Index (HAI) measures the financial ability of a typical household to purchase an existing home in an area. A HAI of 100 represents an area that on average has sufficient household income to qualify for a loan on a home valued at the median home price. An index greater than 100 suggests homes are easily afforded by the average area resident. A HAI less than 100 suggests that homes are less affordable. The housing affordability index is not applicable in areas with no households or in predominantly rental markets . Esri’s home value estimates cover owner-occupied homes only.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Los Angeles Index of Displacement PressureThe Los Angeles Index of Displacement Pressure combines measures that past research efforts and our own original research have shown correlate with future change and displacement pressure. Created in 2015/2016, the index primarily uses data from 2012-2015.These seven measures are applied at the Census Tract level for tracts where >=40% of households earn less than the City's median income. The measures are grouped into two classes: change factors and displacement pressure factors.Change factor measures are those that suggest future revitalization is likely due to investment, projected housing price gains, and proximity to recently changed areas. On the other hand, displacement pressure factors capture areas with a high concentration of existing residents who may have difficulty absorbing massive rent increases that often accompany revitalization. The Los Angeles Index of Displacement Pressure captures the intersection between these two classes.Change Measures Transportation InvestmentMeasure 1: Distance to current rail stations (within a 1/2 mile radius. Tracts beyond 1/2 mile receive no score for this measure). Source: LA MetroMeasure 2: Distance to rail stations under construction/recently opened in 2016 (within a 1/2 mile radius. Tracts beyond 1/2 mile receive no score for this measure)Source: LA Metro Proximity to Rapidly Changing NeighborhoodsMeasure 3: Distance to the closest "top tier" changing neighborhood, as defined by the Los Angeles Index of Neighborhood Change (within a 1 mile radius. Tracts beyond 1 mile receive no score for this measure)Source: The Los Angeles Index of Neighborhood Change Housing MarketMeasure 4: Change in housing price projections from 2015 to 2020 Source: ESRI Community Analyst Displacement Pressure FactorsMeasure 5: Percent of households that rentSource: American Community Survey, Five-Year Estimate, 2014Measure 6: Percent of households that are extremely rent burdened (pay >=50% of household income on rent)Source: American Community Survey, Five-Year Estimate, 2014Measure 7: The number of affordable properties and housing units that are due to expire by 2023.Source: The Los Angeles Housing Element, 2012Date updated: April 7, 2018Refresh rate: Never - Historical data
Housing burden is defined as spending 30% or more of monthly household income on housing. A small number of households without housing cost or income data were excluded from analyses.Given the high cost of housing in Los Angeles County, many residents spend a sizable portion of their incomes on housing every month and are therefore susceptible to significant housing burden. Housing burden disproportionately affects low-income individuals, renters, and communities of color. Housing burden can negatively impact health by forcing individuals and families into low quality or unsafe housing, by causing significant stress, and by limiting the amount of money people have available to spend on other life necessities, such as food or healthcare. It is also an important risk factor for homelessness.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Los Angeles Index of Neighborhood Change is a tool that allows users to explore the extent to which Los Angeles Zip Codes have undergone demographic change from 2000 to 2014. Created in 2015/2016, the data comes from 2000, 2005, 2013, and 2014. Please read details about each measure for exact years.Index scores are an aggregate of six demographic measures indicative of gentrification. The measures are standardized and combined using weights that reflect the proportion of each measure that is statistically significant.Measure 1: Percent change in low/high IRS filer ratio. For the purposes of this measure, High Income = >$75K Adjust Gross Income tax filer and Low Income = <$25k filers who also received an earned income tax credit. Years Compared for Measure 1: 2005 and 2013 | Source: IRS Income Tax Return DataMeasure 2: Change in percent of residents 25 years or older with Bachelor's Degrees or HigherMeasure 3: Change in percent of White, non-Hispanic/Latino residentsMeasure 4: Percent change in median household income (2000 income is adjusted to 2014 dollars)Measure 5: % Change in median gross rent (2000 rent is adjusted to 2013/2014 dollars)Measure 6: Percent change in average household size Year Compared for Measures 2-5: 2000 and 2014, Measure 6: 2013Sources: Decennial Census, 2000 | American Community Survey (5-Year Estimate, 2009-2013; 2010; 2014)Date Updated: December 13, 2016Refresh Rate: Never - Historical data
Dataset contains the percent of denied mortgages based on the type of dwelling the applicant is applying for and disaggregated by race. Each cell represents the denial rate within that column's race/ethnicity category's total applications. Data pulled from the Consumer Financial Protection Bureau, collected by the Home Mortgage Disclosure Act, which requires many financial institutions to maintain, report, and publicly disclose information about mortgages.
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License information was derived automatically
2020 Foreclosure Properties registered with the LAHD from January 1, 2020 through December 31, 2020.
This dataset provides information about the number of properties, residents, and average property values for Grey Drive cross streets in Los Angeles, CA.
This dataset provides information about the number of properties, residents, and average property values for Cresthill Road cross streets in Los Angeles, CA.
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CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
In October 2015, Mayor Garcetti released Executive Directive 13, Support for Affordable Housing (ED 13). ED 13 is a “Back to Basics” operational directive that helps streamline the development of critical new housing developments that address our housing shortage.
This dataset tracks the City's progress towards the goals outlined in the directive: (1) Permitting 100,000 new units from the start of Mayor Garcetti's administration through the end of fiscal year 2021, and (2) Building or preserving 15,000 affordable housing units for low-income households in this same time period.