Empowered by Tyler Technologies
Refine Results

The population rate of change of Indian Hills, TX was 10.58% in 2018.

Population

Population Change

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Demographics and Population Datasets Involving Indian Hills, TX

  • API

    CPI 1.1 Texas Child Population (ages 0-17) by County 2014-2023

    data.texas.gov | Last Updated 2024-09-05T21:23:24.000Z

    As recommended by the Health and Human Services Commission (HHSC) to ensure consistency across all HHSC agencies, in 2012 DFPS adopted the HHSC methodology on how to categorize race and ethnicity. As a result, data broken down by race and ethnicity in 2012 and after is not directly comparable to race and ethnicity data in 2011 and before. The population totals may not match previously printed DFPS Data Books. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but may cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Children, to be recalculated. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. Current population estimates and projections data as of December 2020. Visit dfps.texas.gov for information on all DFPS programs.

  • API

    National Immunization Survey Adult COVID Module (NIS-ACM): COVIDVaxViews| Data | Centers for Disease Control and Prevention (cdc.gov)-Archived

    data.cdc.gov | Last Updated 2024-01-24T15:02:36.000Z

    National Immunization Survey Adult COVID Module (NIS-ACM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent, and other behavioral indicators, by demographics and other characteristics.

  • API

    Demographics For Unincorporated Areas In San Mateo County

    datahub.smcgov.org | Last Updated 2018-10-25T21:45:46.000Z

    Demographics, including median income, total population, race, ethnicity, and age for unincorporated areas in San Mateo County. This data comes from the 2012 American Community Survey 5 year estimates DP03 and DP05 files. They Sky Londa area is located within two Census Tracts. The data for Sky Londa is the sum of both of those Census Tracts. Users of this data should take this into account when using data for Sky Londa.

  • API

    National Immunization Survey Adult COVID Module (NIS-ACM): Vaccination Status and Intent by Demographics

    data.cdc.gov | Last Updated 2023-08-03T20:51:46.000Z

    National Immunization Survey Adult COVID Module (NIS-ACM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent by demographics. Following collection of August 2021 survey data, an error in data processing led to incorrect categorization of some survey respondents; some respondents who should have been categorized as MSA: Principal City instead were categorized as MSA: Non-Principal City. Data downloaded during the period September 12, 2021 through September 30, 2021 may have incorrect estimates by MSA status, SVI of county of residence, and political leaning of county of residence.

  • API

    Labor Force Demographic Characteristics by Commuting Mode Split: 2012 - 2016

    data.cambridgema.gov | Last Updated 2024-05-06T21:33:09.000Z

    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

    Workforce Demographic Characteristics by Commuting Mode Split : 2012 - 2016

    data.cambridgema.gov | Last Updated 2024-05-06T21:39:43.000Z

    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

    Austin Crash Report Data - Crash Victim Demographic Records

    datahub.austintexas.gov | Last Updated 2024-10-19T09:06:24.000Z

    This dataset contains crash victim records for crashes which have occurred in Austin, TX in the last ten years. It is one of two datasets which power our Vision Zero Viewer dashboard, available here: https://visionzero.austin.gov/viewer. Crash data may take several weeks to be submitted, reviewed, and finalized for inclusion in this dataset. To provide the most accurate information as possible, we only provide crash data as recent as two weeks old. Please also note that some crash records may take even longer to appear in this dataset, depending on the circumstances of the crash and the ensuing law enforcement investigation. Crash data is obtained from the Texas Department of Transportation (TxDOT) Crash Record Information System (CRIS) database, which is populated by reports submitted by Texas Peace Officers throughout the state, including Austin Police Department (APD). Please note that the data and information on this website is for informational purposes only. While we seek to provide accurate information, please note that errors may be present and information presented may not be complete.

  • API

    Uninsured Population Census Data CY 2009-2014 Human Services

    data.pa.gov | Last Updated 2022-10-18T14:19:11.000Z

    This data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.

  • API

    National Immunization Survey Child COVID Module (NIS-CCM): Vaccination Status and Intent by Demographics | Data | Centers for Disease Control and Prevention (cdc.gov)

    data.cdc.gov | Last Updated 2023-08-03T18:27:46.000Z

    National Immunization Survey Child COVID Module (NIS-CCM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent, and other behavioral indicators, by demographics and other characteristics.

  • API

    National Immunization Survey Adult COVID Module (NIS-ACM): Trends in Vaccination Status and Intent

    data.cdc.gov | Last Updated 2023-08-03T20:51:54.000Z

    National Immunization Survey-Adult COVID Module (NIS-ACM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent by week for the national-level view, and by month for the jurisdiction-level view.