In 2023, there were over **** million White residents of Los Angeles city in California. In comparison, there were ******* Asian residents and ******* Black or African American residents amongst the Los Angeles population in that year.
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License information was derived automatically
Context
The dataset tabulates the population of Los Angeles by race. It includes the population of Los Angeles across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Los Angeles across relevant racial categories.
Key observations
The percent distribution of Los Angeles population by race (across all racial categories recognized by the U.S. Census Bureau): 37.32% are white, 8.51% are Black or African American, 1.16% are American Indian and Alaska Native, 12.03% are Asian, 0.15% are Native Hawaiian and other Pacific Islander, 25.09% are some other race and 15.74% are multiracial.
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
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Graph and download economic data for Population Estimate, Total, Not Hispanic or Latino, Two or More Races, Two Races Including Some Other Race (5-year estimate) in Los Angeles County, CA (B03002010E006037) from 2009 to 2023 about Los Angeles County, CA; Los Angeles; CA; non-hispanic; estimate; persons; 5-year; population; and USA.
Race categories for White, Black, Asian, American Indian or Alaska Native, Native Hawaiian or Pacific Islander, other race, and two or more races are non-Hispanic. Due to rounding, race and ethnicity categories may not sum to 100%. Estimates are based on provisional data and subject to change.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
Context
The dataset tabulates the Los Angeles County population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Los Angeles County.
The dataset will have the following datasets when applicable
Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)
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/.
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 County by race. It includes the distribution of the Non-Hispanic population of Los Angeles County 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 County across relevant racial categories.
Key observations
Of the Non-Hispanic population in Los Angeles County, the largest racial group is White alone with a population of 2.48 million (48.62% 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 County Population by Race & Ethnicity. You can refer the same here
Population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2023 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries as of July 1, 2023. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/)released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Fields:CT20: 2020 Census tractFIP22: 2023 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2023) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP23CSA: 2020 census tract with 2023 city FIPs for incorporated cities and unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP23_AGE_0_4: 2023 population 0 to 4 years oldPOP23_AGE_5_9: 2023 population 5 to 9 years old POP23_AGE_10_14: 2023 population 10 to 14 years old POP23_AGE_15_17: 2022 population 15 to 17 years old POP23_AGE_18_19: 2023 population 18 to 19 years old POP23_AGE_20_44: 2023 population 20 to 24 years old POP23_AGE_25_29: 2023 population 25 to 29 years old POP23_AGE_30_34: 2023 population 30 to 34 years old POP23_AGE_35_44: 2023 population 35 to 44 years old POP23_AGE_45_54: 2023 population 45 to 54 years old POP23_AGE_55_64: 2023 population 55 to 64 years old POP23_AGE_65_74: 2023 population 65 to 74 years old POP23_AGE_75_84: 2023 population 75 to 84 years old POP23_AGE_85_100: 2023 population 85 years and older POP23_WHITE: 2023 Non-Hispanic White POP23_BLACK: 2023 Non-Hispanic African AmericanPOP23_AIAN: 2023 Non-Hispanic American Indian or Alaska NativePOP23_ASIAN: 2023 Non-Hispanic Asian POP23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific IslanderPOP23_HISPANIC: 2023 HispanicPOP23_MALE: 2023 Male POP23_FEMALE: 2023 Female POV23_WHITE: 2023 Non-Hispanic White below 100% Federal Poverty Level POV23_BLACK: 2023 Non-Hispanic African American below 100% Federal Poverty Level POV23_AIAN: 2023 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV23_ASIAN: 2023 Non-Hispanic Asian below 100% Federal Poverty Level POV23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV23_HISPANIC: 2023 Hispanic below 100% Federal Poverty Level POV23_TOTAL: 2023 Total population below 100% Federal Poverty Level POP23_TOTAL: 2023 Total PopulationAREA_SQMil: Area in square mile.POP23_DENSITY: 2023 Population per square mile.POV23_PERCENT: 2023 Poverty rate/percentage.How this data created?Population by age groups, ethnic groups and gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Notes:1. Population and poverty data estimated as of July 1, 2023. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundaries are as of July 1, 2023.
https://www.icpsr.umich.edu/web/ICPSR/studies/36563/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/36563/terms
The Los Angeles County Social Survey (LACSS) continues the Los Angeles Metropolitan Area Studies (LAMAS) and the Southern California Social Surveys (SCSS). The Los Angeles County Social Survey (LACSS) is part of a continuing annual research project supported by the Institute for Social Science Research at the University of California, Los Angeles (UCLA). The LACSS 1995 was conducted between April and July 1995. Los Angeles County residents were asked questions concerning ethnic relations, social dominance, social distance, immigration, affirmative action, employment, and government. A split ballot methodology was utilized concerning the topics of immigration and affirmative action. Respondents were randomly selected to answer a series of questions from one of three ballots. In addition, a different series of social distance questions were asked depending on the respondent's ethnicity. Questionnaires were provided in both English and Spanish languages. Demographic information collected includes race, gender, religion, age, education level, occupation, birth place, political party affiliation and ideology, and origin of ancestry.
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License information was derived automatically
This dataset tracks annual two or more races student percentage from 2009 to 2022 for North Hollywood Senior High School vs. California and Los Angeles Unified School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Historical Dataset of Los Angeles Senior High School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1990-2022),Total Classroom Teachers Trends Over Years (1990-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1991-2022),American Indian Student Percentage Comparison Over Years (2011-2014),Asian Student Percentage Comparison Over Years (1992-2022),Hispanic Student Percentage Comparison Over Years (1992-2022),Black Student Percentage Comparison Over Years (1992-2022),White Student Percentage Comparison Over Years (1990-2022),Two or More Races Student Percentage Comparison Over Years (2009-2022),Diversity Score Comparison Over Years (1992-2022),Free Lunch Eligibility Comparison Over Years (1994-2022),Reduced-Price Lunch Eligibility Comparison Over Years (2001-2022),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2011-2022),Overall School Rank Trends Over Years (2011-2022),Graduation Rate Comparison Over Years (2012-2022)
Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2012 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP12: 2012 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2012) CT10FIP12: 2010 census tract with 2012 city FIPs for incorporated cities and unincorporated areas. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP12_AGE_0_4: 2012 population 0 to 4 years oldPOP12_AGE_5_9: 2012 population 5 to 9 years old POP12_AGE_10_14: 2012 population 10 to 14 years old POP12_AGE_15_17: 2012 population 15 to 17 years old POP12_AGE_18_19: 2012 population 18 to 19 years old POP12_AGE_20_44: 2012 population 20 to 24 years old POP12_AGE_25_29: 2012 population 25 to 29 years old POP12_AGE_30_34: 2012 population 30 to 34 years old POP12_AGE_35_44: 2012 population 35 to 44 years old POP12_AGE_45_54: 2012 population 45 to 54 years old POP12_AGE_55_64: 2012 population 55 to 64 years old POP12_AGE_65_74: 2012 population 65 to 74 years old POP12_AGE_75_84: 2012 population 75 to 84 years old POP12_AGE_85_100: 2012 population 85 years and older POP12_WHITE: 2012 Non-Hispanic White POP12_BLACK: 2012 Non-Hispanic African AmericanPOP12_AIAN: 2012 Non-Hispanic American Indian or Alaska NativePOP12_ASIAN: 2012 Non-Hispanic Asian POP12_HNPI: 2012 Non-Hispanic Hawaiian Native or Pacific IslanderPOP12_HISPANIC: 2012 HispanicPOP12_MALE: 2012 Male POP12_FEMALE: 2012 Female POV12_WHITE: 2012 Non-Hispanic White below 100% Federal Poverty Level POV12_BLACK: 2012 Non-Hispanic African American below 100% Federal Poverty Level POV12_AIAN: 2012 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV12_ASIAN: 2012 Non-Hispanic Asian below 100% Federal Poverty Level POV12_HNPI: 2012 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV12_HISPANIC: 2012 Hispanic below 100% Federal Poverty Level POV12_TOTAL: 2012 Total population below 100% Federal Poverty Level POP12_TOTAL: 2012 Total PopulationAREA_SQMIL: Area in square milePOP12_DENSITY: Population per square mile.POV12_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2012. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Population Estimate, Total, Hispanic or Latino, Two or More Races, Two Races Excluding Some Other Race, and Three or More Races (5-year estimate) in Orange County, CA (B03002021E006059) from 2009 to 2023 about Orange County, CA; Los Angeles; latino; hispanic; CA; estimate; persons; 5-year; population; and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual two or more races student percentage from 2013 to 2023 for Los Angeles Academy Of Arts & Enterprise Charter vs. California and Los Angeles Unified School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual two or more races student percentage from 2009 to 2022 for Alexander Hamilton Senior High School vs. California and Los Angeles Unified School District
This dataset was used to analyze differences in impervious surface levels by race while also accounting for other sociodemographic factors and land use in Los Angeles County. Data was downloaded from the websites of the U.S. Geological Survey, U.S. Census Bureau, and Southern California Association of Governments. Due to redlining and disinvestment in neighborhoods of color, there are generally fewer green spaces and greater urban heat island effects in neighborhoods of color throughout the U.S., as documented in the environmental justice literature. Replacing impervious surfaces like concrete and asphalt with green stormwater infrastructure can help increase green space and reduce urban heat while also meeting local stormwater goals. This research supports existing findings and ties it to the local stormwater context in Los Angeles County. Based on the results of this research, local decision-makers should consider racial demographics when prioritizing where to remove impervious surface and replacing with green stormwater infrastructure.
Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2019 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP19: 2019 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2019) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP19CSA: 2010 census tract with 2019 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP19_AGE_0_4: 2019 population 0 to 4 years oldPOP19_AGE_5_9: 2019 population 5 to 9 years old POP19_AGE_10_14: 2019 population 10 to 14 years old POP19_AGE_15_17: 2019 population 15 to 17 years old POP19_AGE_18_19: 2019 population 18 to 19 years old POP19_AGE_20_44: 2019 population 20 to 24 years old POP19_AGE_25_29: 2019 population 25 to 29 years old POP19_AGE_30_34: 2019 population 30 to 34 years old POP19_AGE_35_44: 2019 population 35 to 44 years old POP19_AGE_45_54: 2019 population 45 to 54 years old POP19_AGE_55_64: 2019 population 55 to 64 years old POP19_AGE_65_74: 2019 population 65 to 74 years old POP19_AGE_75_84: 2019 population 75 to 84 years old POP19_AGE_85_100: 2019 population 85 years and older POP19_WHITE: 2019 Non-Hispanic White POP19_BLACK: 2019 Non-Hispanic African AmericanPOP19_AIAN: 2019 Non-Hispanic American Indian or Alaska NativePOP19_ASIAN: 2019 Non-Hispanic Asian POP19_HNPI: 2019 Non-Hispanic Hawaiian Native or Pacific IslanderPOP19_HISPANIC: 2019 HispanicPOP19_MALE: 2019 Male POP19_FEMALE: 2019 Female POV19_WHITE: 2019 Non-Hispanic White below 100% Federal Poverty Level POV19_BLACK: 2019 Non-Hispanic African American below 100% Federal Poverty Level POV19_AIAN: 2019 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV19_ASIAN: 2019 Non-Hispanic Asian below 100% Federal Poverty Level POV19_HNPI: 2019 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV19_HISPANIC: 2019 Hispanic below 100% Federal Poverty Level POV19_TOTAL: 2019 Total population below 100% Federal Poverty Level POP19_TOTAL: 2019 Total PopulationAREA_SQMIL: Area in square milePOP19_DENSITY: Population per square mile.POV19_PERCENT: Poverty percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2019. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Census 2010 population/demographic data approximated from block groups to LA Neighborhood Councils using Esri software.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual two or more races student percentage from 2019 to 2023 for Port Of Los Angeles High School District vs. California
The Census Bureau (https://www.census.gov/) maintains geographic boundaries for the analysis and mapping of demographic information across the United States. Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau releases the results of this county as demographic data with geographic identifiers so that maps and analysis can be performed on the US population. There are little more Census Tracts within Los Angeles County in 2020 Census TIGER/Line Shapefiles, compared to 2010.Created/Updated: Updated on September 2023, to merged Long Beach Breakwater land-based tracts silver polygons into bigger tract 990300 as per 2022 TIGER Line Shapefiles, and to update Santa Catalina Islands and San Clemente Islands tract boundary based on DPW City boundaries (except 599000 tract in Avalon). Updated on Sep 2022 and Dec 2022, to align tract boundary along city boundaries. Created on March 2021. How was this data created? This geographic file was downloaded from Census Bureau website: https://www2.census.gov/geo/tiger/TIGER2020PL/STATE/06_CALIFORNIA/06037/on February, 2021 and customized for LA County. Data Fields:1. CT20 (TRACTCE20): 6-digit census tract number, 2. Label (NAME20): Decimal point census tract number.
https://www.icpsr.umich.edu/web/ICPSR/studies/7582/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/7582/terms
This data collection contains two data files created from manuscript census returns. Part 1 is an aggregation of social characteristics of Spanish-surnamed and Mexican-born families in the city of Los Angeles from 1844-1880. The data were used to study family composition and socioeconomic mobility. Data items include real property held by head of household (1844, 1850, and 1880 missing), number of children in household, number of adults who were literate in household (no data for 1844), last name of head of household, place of birth of head of household, and occupational category (i.e., rancher or farmer, professional, mercantile, clerk, skilled, and unskilled). Part 2 is composed of data used to study the socioeconomic development of the Mexican-American community in Los Angeles. The main emphasis was on an analysis of literacy, occupational mobility, schooling, family structure, demographic changes, and property mobility. Data items include last name, first name, age, sex, occupational code, real property, personal property, place of birth, literacy, race, head of household, wife of head, child of head, parent of head, sibling of head, and common law spouse. Definitions of family types and discussion of the methodology and rationale used to generate the data in both files can be found in Appendix A of del Castillo, Richard Griswold. "La Raza Hispano Americana: The Emergence of an Urban Culture Among the Spanish Speaking of Los Angeles, 1850-1880." Ph.D. dissertation, University of California, Los Angeles, CA, 1974.
In 2023, there were over **** million White residents of Los Angeles city in California. In comparison, there were ******* Asian residents and ******* Black or African American residents amongst the Los Angeles population in that year.