- 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 Clute, TX was 11,524 in 2018.
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Demographics and Population Datasets Involving Clute, TX
CPI 1.1 Texas Child Population (ages 0-17) by County 2013-2022data.texas.gov | Last Updated 2023-01-30T16:22:35.000Z
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.state.tx.us for information on all DFPS programs.
NYCHA Resident Data Book Summarydata.cityofnewyork.us | Last Updated 2020-02-08T00:56:30.000Z
Contains resident demographic data at a summary level as of January 1, 2019. The Resident Data Book is compiled to serve as an information source for queries involving resident demographic as well as a source of data for internal analysis. Statistics are compiled via HUD mandated annual income reviews involving NYCHA Staff and residents. Data is then aggregated and compiled by development. Each record pertains to a single public housing development.
AmeriCorps Member Race and Ethnicity National Figuresdata.americorps.gov | Last Updated 2021-02-06T01:05:53.000Z
This dataset represents the percent distribution of AmeriCorps member terms which started their service in calendar year 2019 by race and ethnicity. This report excludes AmeriCorps Seniors volunteers. Included are percentage distributions from the United States Census Bureau's 2010-2019 State Population Characteristics dataset.
APS 1.1 Texas Adult Populations at Risk by County/Region FY2013-FY2022data.texas.gov | Last Updated 2023-02-16T15:40:54.000Z
APS investigates allegations of abuse, neglect, and financial exploitation and provides protective services, regardless of race, creed, color, or national origin to people who are: • age 65 or older; • age 18-64 with a mental, physical, or developmental disability that substantially impairs the ability to live independently or provide for their own self-care or protection; or • emancipated minors with a mental, physical, or developmental disability that substantially impairs the ability to live independently or provide for their own self-care or protection. APS clients do not have to meet financial eligibility requirements. The population totals will 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 Population, 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 for all years from 2010 to 2019 as of December 2019.
CPS 2.1 Removals - by Region with Child Demographics FY2013-2022data.texas.gov | Last Updated 2023-02-07T20:25:10.000Z
A removal occurs when CPS determines that a child cannot safely remain in their own home and that DFPS needs to seek legal custody to ensure child safety. Removals can occur in an investigation, family preservation, family substitute care or family reunification stage. Visit dfps.texas.gov for information on CPS Abuse/Neglect Investigations and all DFPS programs.
Bronx Zip Population and Densitybronx.lehman.cuny.edu | Last Updated 2012-10-21T14:06:17.000Z
2010 Census Data on population, pop density, age and ethnicity per zip code
Social Vulnerability Index for Virginia by Census Tract, 2018data.virginia.gov | Last Updated 2022-11-09T20:24:29.000Z
"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
CPI 3.8 Abuse/Neglect Investigations - Victims with Demographics by Region FY2013-FY2022data.texas.gov | Last Updated 2023-01-30T19:04:11.000Z
This chart counts victims in completed investigations. Completed investigations only include those cases conducted as a traditional investigation that were not administratively closed or merged into another stage. An investigation can only be administratively closed if all allegations have a disposition of administrative closure. A completed investigation can include more than one alleged victim. Completed investigations do not include any Alternative Response stages. A confirmed victim on a completed investigation is a child who is a victim on at least one allegation with a disposition of reason to believe. An unconfirmed victim on a completed investigation is a child who was an alleged victim on at least one allegation with a disposition of unable to complete, unable to determine or ruled out. A description of Alternative Response and how it differs from a traditional investigation and the definitions of the different dispositions in a traditional investigation are in the glossary. Visit dfps.state.tx.us for information on CPS Abuse/Neglect Investigations and all DFPS programs.
Indicators of Anxiety or Depression Based on Reported Frequency of Symptoms During Last 7 Daysdata.cdc.gov | Last Updated 2023-02-22T16:39:53.000Z
The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness. The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, gender, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions,
NYSERDA Low- to Moderate-Income New York State Census Population Analysis Dataset: Average for 2013-2015data.ny.gov | Last Updated 2019-11-15T22:30:02.000Z
How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015. Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population. The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight. The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).