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The population density of Taft Southwest, TX was 1,551 in 2018.

Population Density

Population Density is computed by dividing the total population by Land Area Per Square Mile.

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

Geographic and Population Datasets Involving Taft Southwest, 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

    Strategic Measure_Cost of City Services per Capita Adjusted for Inflation (General Fund only)

    datahub.austintexas.gov | Last Updated 2023-04-10T13:40:21.000Z

    This dataset has information about the cost of providing General Fund City services per capita of the Full Purpose City population (SD23 measure GTW.A.4). It provides expense information from the annual approved budget document (General Fund Summary and Budget Stabilization Reserve Fund Summary) and population information from the City Demographer's Full Purpose Population numbers. The Consumer Price Index information for Texas is available through the following Key Economic Indicators dataset: https://data.texas.gov/dataset/Key-Economic-Indicators/karz-jr5v. This dataset can be used to help understand the cost of city services over time. View more details and insights related to this dataset on the story page: https://data.austintexas.gov/stories/s/ixex-hibp

  • API

    CPS 2.4 Children In Legal Responsibility on August 31 by Legal Status and Average Days in Care FY2014-2023

    data.texas.gov | Last Updated 2024-02-12T18:17:38.000Z

    Children in DFPS custody are those for whom a court has appointed DFPS legal responsibility through temporary or permanent managing conservatorship or other court ordered legal basis. This chart includes any child in DFPS custody on August 31 of the fiscal year. A description of the different types of legal statuses is in the CPS glossary: https://www.dfps.texas.gov/About_DFPS/Data_Book/Child_Protective_Services/Resources/glossary.asp Visit dfps.texas.gov for information on Children In Legal Responsibility and all DFPS programs.

  • API

    Demographics Stats at a Glance

    datahub.austintexas.gov | Last Updated 2024-10-24T14:56:11.000Z

    These are the statistics listed in the "Stats at a Glance" section of the City of Austin demographics website: https://demographics-austin.hub.arcgis.com/

  • API

    HE.C.2 Peer Cities Table V3

    datahub.austintexas.gov | Last Updated 2024-10-18T18:24:13.000Z

    PARD’s Long Range Plan for Land, Facilities and Programs, Our Parks, Our Future (adopted November 2019) compared Austin’s park system to five peer cities: Atlanta, GA, Dallas, TX, Portland, OR, San Antonio, TX, and San Diego, CA. The peer cities were selected based on characteristics such as population, size, density, and governance type. Portland and San Diego were selected as aspirational cities known for their park systems. Note that the table below presents each scoring area’s 1 to 100 index, where 100 is the highest possible score.

  • API

    Barton Spring Salamander Counts and Covariates

    datahub.austintexas.gov | Last Updated 2023-04-10T13:39:01.000Z

    Observations of Barton Springs Salamanders at Austin's Barton Springs (a complex of several springs) with abundance as observed by size classes with several covariates. Discharge data from USGS: https://waterdata.usgs.gov/tx/nwis/uv/?site_no=08155500&PARAmeter_cd=00065,00060

  • API

    Strategic Measure_EOA.C.6 Number and percentage of residents that are living in an area considered to be a Complete Community

    datahub.austintexas.gov | Last Updated 2024-10-24T14:35:02.000Z

    This is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics. A resident in a complete community is someone residing in an area that is within a 20 minute walk to multiple essential destinations. Calculation method: This study measured the distance and time it takes for a pedestrian to reach five essential destination, or "indicators," from any point across the city using the existing network of sidewalks and crossings within a 20-minute walk time. Using GIS software, this evaluation resulted in a rasterized overlay of geographic outlines of “walksheds” surrounding each indicator destination. Residential estimates were found using an internal database of residential housing units and applied density assumptions and should not be compared to other demographic datasets. Data was sourced from City of Austin, CapMetro, and Austin ISD. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/rw4g-mrjp

  • API

    Austin Crash Report Data - Crash Victim Demographic Records

    datahub.austintexas.gov | Last Updated 2024-10-26T09:06:00.000Z

    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

    Austin Crash Report Data - Crash Level Records

    datahub.austintexas.gov | Last Updated 2024-10-26T09:05:35.000Z

    This dataset contains traffic crash 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). 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

    Surface Drinking Water Importance - Forests on the Edge_data

    opendata.utah.gov | Last Updated 2024-04-10T19:40:35.000Z

    America’s private forests provide a vast array of public goods and services, including abundant, clean surface water. Forest loss and development can affect water quality and quantity when forests are removed and impervious surfaces, such as paved roads, spread across the landscape. We rank watersheds across the conterminous United States according to the contributions of private forest land to surface drinking water and by threats to surface water from increased housing density. Private forest land contributions to drinking water are greatest in the East but are also important in Western watersheds. Development pressures on these contributions are concentrated in the Eastern United States but are also found in the North-Central region, parts of the West and Southwest, and the Pacific Northwest; nationwide, more than 55 million acres of rural private forest land are projected to experience a substantial increase in housing density from 2000 to 2030. Planners, communities, and private landowners can use a range of strategies to maintain freshwater ecosystems, including designing housing and roads to minimize impacts on water quality, managing home sites to protect water resources, and using payment schemes and management partnerships to invest in forest stewardship on public and private lands.This data is based on the digital hydrologic unit boundary layer to the Subwatershed (12-digit) 6th level for the continental United States. To focus this analysis on watersheds with private forests, only watersheds with at least 10% forested land and more than 50 acres of private forest were analyzed. All other watersheds were labeled “Insufficient private forest for this analysis"and coded -99999 in the data table. This dataset updates forest and development statistics reported in the the 2011 Forests to Faucet analysis using 2006 National Land Cover Database for the Conterminous United States, Grid Values=41,42,43,95. and Theobald, Dr. David M. 10 March 2008. bhc2000 and bhc2030 (Housing density for the coterminous US in 2000 and 2030, respectively.) Field Descriptions:HUC_12: Twelve Digit Hydrologic Unit Code: This field provides a unique 12-digit code for each subwatershed.HU_12_DS: Sixth Level Downstream Hydrologic Unit Code: This field was populated with the 12-digit code of the 6th level hydrologic unit that is receiving the majority of the flow from the subwatershed.IMP1: Index of surface drinking water importance (Appendix Map). This field is from the 2011 Forests to Faucet analysis and has not been updated for this analysis.HDCHG_AC: Acres of housing density change on private forest in the subwatershed. HDCHG_PER: Percent of the watershed to experience housing density change on private forest. IMP_HD_PFOR: Index Private Forest importance to Surface Drinking Water with Development Pressure - identifies private forested areas important for surface drinking water that are likely to be affected by future increases in housing density, Ptle_IMP_HD: Private Forest importance to Surface Drinking Water with Development Pressure (Figure 7), percentile. Ptle_HDCHG: Percentage of each subwatershed to Experience an increase in House Density in Private Forest (Figure 6), percentile. FOR_AC: Acres forest (2006) in the subwatershed. PFOR_AC: Acres private forest (2006) in the subwatershed. PFOR_PER: Percent of the subwatershed that is private forest. HU12_AC: Acreage of the subwatershedFOR_PER: Percent of the subwatershed that is forest. PFOR_IMP: Index of Private Forest Importance to Surface Drinking Water. .Ptle_PFIMP: Private forest importance to surface drinking water(Figure 4), percentile. TOP100: Top 100 subwatersheds. 50 from the East, 50 from the west (using the Mississippi River as the divide.) (Figure 8)TOP50EW: 1 = EAST; 2=WESTPoint of Contact: Rebecca Lilja GIS SpecialistForest ServiceNortheastern Area State and Private Forestryp: 603-868-7627 c: 603-953-4307 rlilja@fs.fed.us271 Mast Rd Durham, NH 03824