This file contains a list of taxpayers who hold an active sales tax permit under Tax Code Chapter 151, Subchapter F. The file includes taxpayer and outlet information.

See https://comptroller.texas.gov/about/policies/privacy.php for more information on our agency’s privacy and security policies

This dataset was created by the Transportation Planning and Programming (TPP) Division of the Texas Department of Transportation (TxDOT) for planning and asset inventory purposes, as well as for visualization and general mapping. County boundaries were digitized by TxDOT using USGS quad maps, and converted to line features using the Feature to Line tool. This dataset depicts a generalized coastline.Update Frequency: As NeededSource: Texas General Land OfficeSecurity Level: PublicOwned by TxDOT: FalseRelated LinksData Dictionary PDF [Generated 2025/03/14]

Texas county centroid latitude and longitude map data.

About this dataset

Context

The dataset tabulates the population of Texas County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Texas County across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of male population, with 54.1% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Texas County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Texas County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Texas County Population by Gender. You can refer the same here

Point features representing assigned site or structure addresses within the city. Each point corresponds to a physical location where an address has been established for mail delivery, utility service, emergency response, permitting, or other municipal functions. The dataset supports address lookup, geocoding, mapping, and integration with land records, parcels, and transportation networks. Attributes typically include the full address and related components (house number, street name, unit, city, ZIP code).Data UpdatesAddress points are added or changed after Addressing memorandums are sent out by City of Midland Addressing.Coverage AreaMidland County, Texas and City of Midland, Texas (city limits)Coordinate SystemNAD 1983 StatePlane Central Texas FIPS 4203

Vector polygon map data of city limits from Houston, Texas containing 731 features.

City limits GIS (Geographic Information System) data provides valuable information about the boundaries of a city, which is crucial for various planning and decision-making processes. Urban planners and government officials use this data to understand the extent of their jurisdiction and to make informed decisions regarding zoning, land use, and infrastructure development within the city limits.

By overlaying city limits GIS data with other layers such as population density, land parcels, and environmental features, planners can analyze spatial patterns and identify areas for growth, conservation, or redevelopment. This data also aids in emergency management by defining the areas of responsibility for different emergency services, helping to streamline response efforts during crises..

This city limits data is available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

County feature class used in the TEA School District Locator

Vector polygon map data of property parcels from Fort Worth, Texas containing 651,519 features.

Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

ALL FILES ARE LOCATED AT MY REPOSITORY: https://github.com/christianio123/TexasAttendance

Context

I was curious about factors affecting school attendance so I gathered data from school districts around Texas to have a better idea.

Topic/Purpose

The purpose of the project is to help determine factors associated with student attendance in the state of Texas. No population is targeted as an audience for the project, however, anyone associated in education may find the dataset used (and other data attained but not used) helpful in any questions they may have regarding student attendance in Texas for the first two months of the 2020-2021 academic school year. This topic was targeted specifically due to the abnormalities in the current academic school year.

Data

Daily Student Attendance

Majority of the data in this project was collected by school districts around the state of Texas, public census information, and public COVID 19 data. To attain student attendance information, an email was sent out to 40 school districts around the state of Texas on November 2nd, 2020 using the Freedom of Information Act (FOIA). Of those districts, 19 responded with the requested data, while other districts required purchase of the data due to the number of hours associated with labor. Due to ambiguity in the original message sent to districts, varying types of data were collected. The major difference between the data received was the “daily” records of student attendance and a “summary” of student attendance records so far, this academic school year. School districts took between 10 to 15 business days to respond, not including the holidays. The focus of this project is “daily student attendance” in order to find relationships or any influences from external or internal factors on any given school day. Therefore, of the 19 school districts that responded, 11 sent the appropriate data.
The 11 school districts that sent data were (1) Conroe ISD, (2) Cypress-Fairbanks ISD, (3) Floydada ISD, (4) Fort Worth ISD, (5) Pasadena ISD, (6) Snook ISD, (7) Socorro ISD, (8) Klein ISD, (9) Garland ISD, (10) Dallas ISD, and (11) Katy ISD. However, even within these datasets, there were discrepancies, that is, three school districts sent daily attendance data including student grade level but one school district did not include any other information. Also, of the 11 school districts, nine school districts included student attendance broken down by school while three other school districts only had student attendance with no other attributes. This information is important to explain certain steps in analysis preparation later. Variables used from school district datasets included (a) dates, (b) weekdays, (c) school name, (d) school type, (e) district, and (f) grade level.

School Information, County Description, Metropolitan vs. Non-Metropolitan

  In addition to daily student attendance data, two other datasets were used from the Texas Education Agency with data about each school and school district. In one dataset, “Current Schools”, information about each school in the state of Texas was given such as address, principal, county name, district number and much more as of May 2020. From this dataset, variables selected include (a) school name, (b) school zip, (3) district number, (4) and school type. In the second dataset, “District Type”, attributes of each school district were given such as whether the school district was considered major urban, independent town, or a rural area. From “District Type” dataset, selected variables used were (a) district, district number, Texas Education Agency (TEA) description, and National Center of Education Statistics (NCES). To determine if a county is metropolitan or non-metropolitan, a dataset from the Texas Health and Human Services was used. Selected variables from this dataset include (a) county name and (b) metro area. 

Other Factors: COVID-19

 Student attendance has been noticeably different this academic school year, therefore live COVID-19 data was attained from the New York Times to examine for any relationship. This dataset is updated daily with data being available in three formats (country, state, and county). From this dataset, variables selected were both COVID-19 cases by state, and by county.

Other Factors: Demographics

Each school has a unique student population, therefore census data from 2018 (with best estimate of today’s current population) was used to find the makeup of the population surrounding a school by zip code. From the census data, variables selected were zip code, race/ethnicity, medium income, unemployment rate, and education. These variables were selected to determine differences between school attendance based on the makeup of the population surrounding the school.

Other Factors: Weather

  Weather seems to have an impact on student attendance at schools, so weather data has been included based on county measures.

Street Name Master List - contains all the reserved and active street names.

Modeled on the Community Survey of the Project on Human Development in Chicago Neighborhoods, the proposed project collected survey data from random samples of individuals from a random sample of “neighborhood clusters” in El Paso County, Texas. Neighborhood clusters consist of geographically contiguous and socially similar census tracts and for El Paso will be determined by a combination of the local knowledge possessed by the project’s researchers, preliminary analyses of the most recent census data regarding the distributions of immigrant status, language use, year of entry, and aspects of economic disadvantage as well as obvious boundaries (such as Interstates, major roads, mountains, and military installations). The project used a sampling frame of neighborhood clusters in El Paso County stratified by measures of immigrant concentration (e.g., generational status, length of time since immigration) and socio-economic status. The project then employed Cole Lists, a company that provides consumer information for direct marketers, to obtain a list of all residential addresses in El Paso County by census tract. From each sampled neighborhood cluster, 30 residences were selected using a systematic random sampling procedure (a random start determined from a table of random numbers and then selecting every kth address. Each selected residence was mailed a notification letter, printed in English and in Spanish, regarding participation in the project and which specified that a trained interviewer will personally visit to determine which adult resident(s), if any, are willing to participate. For residences that agreed to participate, the adult resident who had the most recent birthday was selected for actual participation. These respondents received an incentive of $20. In face-to-face interviews, trained interviewers recorded each respondent’s answers on a paper form and later manually entered this information into a computer file using spreadsheet software.

Total vehicle registration counts per month by county

The purpose of the medication-assisted treatment (MAT) facility maps is to identify areas on a state-by-state basis that may be potentially underserved by existing treatment facilities. The maps are created with a methodology that seeks to include the highest potential need areas from individual counties so that county-level stakeholders are also informed. The maps are meant to be used as a tool for policy makers to determine potentially underserved areas—not as a definitive representation of these areas.

Do not use this data to make zoning determinations. This data does not show all zoning regulations for an address, including overlays and situations where an address has more than one zoning. Also, the data may be out of date. Use the interactive mapping application https://maps.austintexas.gov/GIS/PropertyProfile/ to make zoning determinations, and call 311 if you have questions about zoning. Zoning only applies to addresses within the City of Austin city limits. This dataset is a list of addresses with their zoning provided to answer questions such as "what property addresses have CS zoning." This data is derived from GIS layer for address and zoning. The place_id field is provided for linking to the addresses GIS layer. This product is produced by the City of Austin for informational purposes. No warranty is made they City of Austin regarding specific accuracy or completeness.

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.texas.gov for information on CPS Abuse/Neglect Investigations and all DFPS programs.

An application used by the public to locate grocery stores, pharmacies, general stores, and food pantries in their community.To get started…1. Enter your address in the search box or click on a location directly on the map.2. Optionally, adjust the buffer slider to see a larger list of potential food services.3. Select the closest food service from the list and review the information provided.

ABOUT THIS CHART Allegation Disposition (Findings) Codes:

Valid. Based on the standard of preponderance of the evidence, it is more likely than not that the maltreatment occurred.

Invalid. Based on the standard of preponderance of the evidence, it is more likely than not that the maltreatment did not occur.

Unable to Determine. A preponderance of the available evidence is insufficient to support a finding of Valid or Invalid.

Other. The allegation disposition Other is used when an investigation of the allegation was not completed for some reason, e.g. clients died or cases were misclassified.

1. Family Violence is indicated when a validated investigation has a relative perpetrator, excluding those where financial exploitation is the only confirmed allegation.

2. Beginning in Fiscal Year 2015, services provided during the investigation are documented in the investigation stage and not in a separate service stage.

3. The "Other" Disposition category refers to those investigations that workers could not complete, e.g. clients died or cases were misclassified.

4. The population totals do not match prior DFPS Data Books, printed or online. 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 will 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 for all years from 2014 to 2023 as of December 2023.

Visit dfps.state.tx.us for information on all DFPS programs.

This is a dataset containing what the Texas Water Development Board (TWDB) in Austin, Texas considers the 9 Major aquifers of Texas. Lines were digitized from the Bureau of Economic Geology's Geologic Atlas Sheets (GAT) at 1:250,000 scale. Work started in January 1990 and was completed in May 1990. All digitizing was done at the USGS office in Austin, Texas using Arc/Info. REVISIONS MADE TO THE MAJOR AQUIFERS FOR THE 2007 STATE WATER PLAN: The Edwards aquifer southern boundary has been updated based on new geochemical data. The boundary of the 1,000-mg/L line of equal dissolved solids concentration has been revised and moved both to the north and south of the previous boundary. More information on the new aquifer boundary can be found in the Texas 2007 State Water plan at http://www.twdb.state.tx.us/home/index.asp. In general, the Pecos Valley aquifer is defined by: (1) the occurrence of structural highs that have the potential to form barriers to groundwater flow and (2) the spatial extent of the Pecos Valley sediment. The Pecos Valley aquifer boundary differs from its former boundary in two ways. First, we revised the aquifer boundary, extending the aquifer into New Mexico to coincide with perceived hydrologic boundaries. Second, the old aquifer boundary excluded parts of Loving, Winkler, Ward, Pecos, and Crane counties where the alluvium is thin. This presents a problem to modeling groundwater flow because it incorrectly restricts access to the Pecos River, the main discharge zone. The new aquifer boundary better represent the geology as indicated by the 1:250,000 maps of the Geologic Atlas of Texas by including these areas of thinner alluvium. More information on the new aquifer boundary can be found in the Texas 2007 State Water plan at http://www.twdb.state.tx.us/home/index.asp. Aware of reports that not all of the mapped Seymour Aquifer held water, TWDB reviewed well information to determine which parts of the aquifer hold water and which parts do not. This review was done prior to developing the groundwater availability model for the Seymour Aquifer. In the process of developing the model, additional changes were made to the aquifer’s extent. Therefore, TWDB has changed the boundary so that only those sediments that are known to hold groundwater are part of the Seymour Aquifer More information on the new aquifer boundary can be found in the Texas 2007 State Water plan at http://www.twdb.state.tx.us/home/index.asp. The Trinity Aquifer extends beneath the Edwards (Balcones Fault Zone) Aquifer ending in the subsurface toward the west in eastern Uvalde County. This subsurface boundary in Uvalde County appears to coincide with the Sabinal River and, therefore, has a great amount of sinuosity and detail. Groundwater in the Trinity Aquifer in Uvalde County presumably flows beneath the Edwards (Balcones Fault Zone) Aquifer toward the south, in the same direction of the Sabinal River, which is probably why TWDB chose the river as the subsurface boundary of the aquifer. However, the boundary has much greater detail than what is known about the groundwater flow line. Therefore, TWDB has smoothed the shape of this line to better reflect the knowledge of its position. More information on the new aquifer boundary can be found in the Texas 2007 State Water plan at http://www.twdb.state.tx.us/home/index.asp. * The Edwards-Trinity Aquifer (outcrop) lines in West Texas were adjusted to lie adjacent to the updated Pecos Valley aquifer lines. Also, a small part of the outcrop was reclassified to subcrop in order to show the adjusted outcrop of the Pecos Valley aquifer which lies on top of the Edwards-Trinity in northern Pecos County. Also, a small part of the Ogallala aquifer in West Texas (specifically Andrews and Ector counties) was adjusted to lie adjacent to the updated Pecos Valley and Edwards-Trinity aquifer lines.

This map supports the LPHCP address locator application.

This layer contains the data for the stormwater quality ponds in the City of Round Rock, located in Williamson County, Texas. This layer is part of an original dataset provided and maintained by the City of Round Rock GIS/IT and Public Works Departments. The data in this layer are represented as polygons. A stormwater quality pond is a man-made pond which is utilized by the city or private companies to collect water and test it to determine the water quality. Information about the address, pond area, condition, installation year, ownership, and any relevant comments are included in this layer.