- What is the Population Rate of Change?
- What is the Population Density?
- What is the Land Area?
- What is the Percent who did not finish the 9th grade?
- What is the Median Earnings?
- What is the Number of Employees?
- What is the Crime incident count?
- What is the Water Area?
- What is the High School Graduation Rate?
- What is the Median Female Earnings?
The population count of Huntington Park, CA was 58,694 in 2018.
Demographics and Population Datasets Involving Huntington Park, CA
- API performance.smcgov.org | Last Updated 2016-08-31T20:40:07.000Z
Violent and property crime rates per 100,000 population for San Mateo County and the State of California. The total crimes used to calculate the rates for San Mateo County include data from: Sheriff's Department Unincorporated, Atherton, Belmont, Brisbane, Broadmoor, Burlingame, Colma, Daly City, East Palo Alto, Foster City, Half Moon Bay, Hillsborough, Menlo Park, Millbrae, Pacifica, Redwood City, San Bruno, San Carlos, San Mateo, South San Francisco, Bay Area DPR, BART, Union Pacific Railroad, and CA Highway Patrol.
- API healthstat.dph.sbcounty.gov | Last Updated 2019-03-13T19:07:43.000Z
Percent of People who Cannot Afford to Feed Themselves Sufficiently. U.S. Census Bureau, Current Population Survey, December Supplement (AKA USDA Food Security Supplement). Dissected by Year, Geographic Area, Age Category, and Race/Ethnicity.
- API data.virginia.gov | Last Updated 2023-05-22T14:49:26.000Z
"ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) created Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI or simply SVI, hereafter) to help public health officials and emergency response planners identify and map the communities that will most likely need support before, during, and after a hazardous event. SVI indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking." For more see https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html
- API data.countyofnapa.org | Last Updated 2023-08-10T21:09:02.000Z
Report P-3: Population Projections Race/Ethnicity and Sex by Individual Years of Age, 2010 to 2060 California (2019 Baseline) Data Notes: "The California Department of Finance (DOF), Demographic Research Unit is responsible by statute for maintaining postcensal population projections which are calculated using the demographic balancing equation: Current Population = Previous Population + (Births - Deaths) +Net Migration This method calculates the population in the target year by starting with the population from the previous year, adding natural increase (births minus deaths) and net migration that occurred during the time period between the two years. The births, deaths, and migration anticipated during the time period are called the components of change. A cohort-component method traces people born in a given year throughout their lives. As each year passes, cohorts change due to the mortality and migration assumptions. Applying fertility assumptions to women of childbearing age forms new cohorts at age zero. These 2019 baseline projections incorporate the latest historical population, birth, death, and migration data available as of July 1, 2020. Historical trends from 1990 through 2020 for births, deaths, and migration are examined. County populations by age, sex, and race/ethnicity are projected to 2060. The county projections are then summed to obtain data for the state. " View the Methodology at: https://dof.ca.gov/Forecasting/Demographics/Projections/ Published by: Demographic Research Unit Department of Finance Website: www.dof.ca.gov/Forecasting/Demographics/Projections/ Phone: 916-323-4086 Suggested Citation California Department of Finance. Demographic Research Unit. Report P-3: Population Projections, California, 2010-2060 (Baseline 2019 Population Projections; Vintage 2020 Release). Sacramento: California. July 2021. Data dictionary: https://dof.ca.gov/wp-content/uploads/sites/352/Forecasting/Demographics/Documents/P3_Dictionary.txt
- API data.cambridgema.gov | Last Updated 2023-08-01T12:47:57.000Z
This data set provides demographic and journey to work characteristics of the Cambridge Labor Force by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time leaving home, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Labor Force consist of all persons who live in Cambridge who work or are actively seeking employment. For more information on Journey to Work data in Cambridge, please see the report Moving Forward: 2020 - https://www.cambridgema.gov/-/media/Files/CDD/FactsandMaps/profiles/demo_moving_forward_2020.pdf
- API data.cambridgema.gov | Last Updated 2023-08-01T12:47:27.000Z
This data set provides demographic and journey to work characteristics of the Cambridge Workforce by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time arriving at work, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Workforce consist of all persons who work in Cambridge, regardless of home location. For more information on Journey to Work data in Cambridge, please see the report Moving Forward: 2020 - https://www.cambridgema.gov/-/media/Files/CDD/FactsandMaps/profiles/demo_moving_forward_2020.pdf
- API data.orcities.org | Last Updated 2017-01-09T17:17:43.000Z
Data from the American Communities Survey 2014. This data includes information on household income, city industries composition, and class of workers.
- API data.sfgov.org | Last Updated 2023-10-02T19:21:58.000Z
<strong>A. SUMMARY</strong> This dataset includes unintentional drug overdose death rates by race/ethnicity by year. This dataset is created using data from the California Electronic Death Registration System (CA-EDRS) via the Vital Records Business Intelligence System (VRBIS). Substance-related deaths are identified by reviewing the cause of death. Deaths caused by opioids, methamphetamine, and cocaine are included. Homicides and suicides are excluded. Ethnic and racial groups with fewer than 10 events are not tallied separately for privacy reasons but are included in the “all races” total. Unintentional drug overdose death rates are calculated by dividing the total number of overdose deaths by race/ethnicity by the total population size for that demographic group and year and then multiplying by 100,000. The total population size is based on estimates from the <u><a href="https://www.census.gov/data/tables/time-series/demo/popest/2020s-counties-detail.html">US Census Bureau County Population Characteristics for San Francisco, 2022 Vintage</a></u> by age, sex, race, and Hispanic origin. These data differ from the data shared in the <u><a href="https://data.sfgov.org/dataset/Preliminary-Accidental-Drug-Overdose-Deaths/jxrr-bmra"> Preliminary Unintentional Drug Overdose Death by Year dataset </a></u> since this dataset uses finalized counts of overdose deaths associated with cocaine, methamphetamine, and opioids only. <strong>B. HOW THE DATASET IS CREATED</strong> This dataset is created by copying data from the <u><a href="https://www.csuhsf.org/substance-use-trends-san-francisco">Annual Substance Use Trends in San Francisco report</a></u> from the San Francisco Department of Public Health Center on Substance Use and Health. <strong>C. UPDATE PROCESS</strong> This dataset will be updated annually, in September. <strong>D. HOW TO USE THIS DATASET</strong> N/A <strong>E. RELATED DATASETS</strong> <u><a href="https://data.sfgov.org/d/ed3a-sn39">Overdose-Related 911 Responses by Emergency Medical Services</a></u> <u><a href="https://data.sfgov.org/d/jxrr-bmra">Preliminary Unintentional Drug Overdose Deaths</a></u> <u><a href="https://data.sfgov.org/d/ubf6-e57x">San Francisco Department of Public Health Substance Use Services</a></u>
- API data.kcmo.org | Last Updated 2021-11-12T14:15:42.000Z
basic characteristics of people and housing for individual 2010 census block groups
- API data.bayareametro.gov | Last Updated 2019-08-13T16:16:34.000Z
VITAL SIGNS INDICATOR Income (EC4) FULL MEASURE NAME Household income by place of residence LAST UPDATED May 2019 DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis. DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org U.S. Census Bureau: American Community Survey Form B19013 (2006-2017; place of residence) http://api.census.gov Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2017; specific to each metro area) http://data.bls.gov CONTACT INFORMATION firstname.lastname@example.org METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income. Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.