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TwitterA detailed explanation of how this dataset was put together, including data sources and methodologies, follows below.Please see the "Terms of Use" section below for the Data DictionaryDATA ACQUISITION AND CLEANING PROCESSThis dataset was built from 5 separate datasets queried during the months of April and May 2023 from the Census Microdata System (link below):https://data.census.gov/mdat/#/All datasets include information on Property Value (VALP) by: Educational Attainment (SCHL), Gender (SEX), a specified race or ethnicity (RAC or HISP), and are grouped by Public Use Microdata Areas (PUMAS). PUMAS are geographic areas created by the Census bureau; they are weighted by land area and population to facilitate data analysis. Data also Included totals for the state of New Mexico, so 19 total geographies are represented. Datasets were downloaded separately by race and ethnicity because this was the only way to obtain the VALP, SCHL, and SEX variables intersectionally with race or ethnicity data. Datasets were downloaded separately by race and ethnicity because this was the only way to obtain the VALP, SCHL, and SEX variables intersectionally with race or ethnicity data. Cleaning each dataset started with recoding the SCHL and HISP variables - details on recoding can be found below.After recoding, each dataset was transposed so that PUMAS were rows and SCHL, VALP, SEX, and Race or Ethnicity variables were the columns.Median values were calculated in every case that recoding was necessary. As a result, all Property Values in this dataset reflect median values.At times the ACS data downloaded with zeros instead of the 'null' values in initial query results. The VALP variable also included a "-1" variable to reflect N/A values (details in variable notes). Both zeros and "-1" values were removed before calculating median values, both to keep the data true to the original query and to generate accurate median values.Recoding the SCHL variable resulted in 5 rows for each PUMA, reflecting the different levels of educational attainment in each region. Columns grouped variables by race or ethnicity and gender. Cell values were property values.All 5 datasets were joined after recoding and cleaning the data. Original datasets all include 95 rows with 5 separate Educational Attainment variables for each PUMA, including New Mexico State totals.Because 1 row was needed for each PUMA in order to map this data, the data was split by Educational Attainment (SCHL), resulting in 110 columns reflecting median property values for each race or ethnicity by gender and level of educational attainment.A short, unique 2 to 5 letter alias was created for each PUMA area in anticipation of needing a unique identifier to join the data with. GIS AND MAPPING PROCESSA PUMA shapefile was downloaded from the ACS site. The Shapefile can be downloaded here: https://tigerweb.geo.census.gov/arcgis/rest/services/TIGERweb/PUMA_TAD_TAZ_UGA_ZCTA/MapServerThe DBF from the PUMA shapefile was exported to Excel; this shapefile data included needed geographic information for mapping such as: GEOID, PUMACE. The UIDs created for each PUMA were added to the shapefile data; the PUMA shapfile data and ACS data were then joined on UID in JMP.The data table was joined to the shapefile in ARC GiIS, based on PUMA region (specifically GEOID text).The resulting shapefile was exported as a GDB (geodatabase) in order to keep 'Null' values in the data. GDBs are capable of including a rule allowing null values where shapefiles are not. This GDB was uploaded to NMCDCs Arc Gis platform. SYSTEMS USEDMS Excel was used for data cleaning, recoding, and deriving values. Recoding was done directly in the Microdata system when possible - but because the system is was in beta at the time of use some features were not functional at times.JMP was used to transpose, join, and split data. ARC GIS Desktop was used to create the shapefile uploaded to NMCDC's online platform. VARIABLE AND RECODING NOTESTIMEFRAME: Data was queried for the 5 year period of 2015 to 2019 because ACS changed its definiton for and methods of collecting data on race and ethinicity in 2020. The change resulted in greater aggregation and les granular data on variables from 2020 onward.Note: All Race Data reflects that respondants identified as the specified race alone or in combination with one or more other races.VARIABLE:ACS VARIABLE DEFINITIONACS VARIABLE NOTESDETAILS OR URL FOR RAW DATA DOWNLOADRACBLKBlack or African American ACS Query: RACBLK, SCHL, SEX, VALP 2019 5yrRACAIANAmerican Indian and Alaska Native ACS Query: RACAIAN, SCHL, SEX, VALP 2019 5yrRACASNAsian ACS Query: RACASN, SCHL, SEX, VALP 2019 5yrRACWHTWhite ACS Query: RACWHT, SCHL, SEX, VALP 2019 5yrHISPHispanic Origin ACS Query: HISP ORG, SCHL, SEX, VALP 2019 5yrHISP RECODE: 24 original separate variablesThe Hispanic Origin (HISP) variable originally included 24 subcategories reflecting Mexican, Central American, South American, and Caribbean Latino, and Spanish identities from each Latin American counry. 7 recoded VariablesThese 24 variables were recoded (grouped) into 7 simpler categories for data analysis: Not Spanish/Hispanic/Latino, Mexican, Caribbean Latino, Central American, South American, Spaniard, All other Spanish/Hispanic/Latino Female. Not Spanish/Hispanic/Latino was not really used in the final dataset as the race datasets provided that information.SCHLEducational Attainment25 original separate variablesThe Educational Attainment (SCHL) variable originally included 25 subcategories reflecting the education levels of adults (over 18) surveyed by the ACS. These include: Kindergarten, Grades 1 through 12 separately, 12th grade with no diploma, Highschool Diploma, GED or credential, less than 1 year of college, more than 1 year of college with no degree, Associate's Degree, Bachelor's Degree, Master's Degree, Professional Degree, and Doctorate Degree.SCHL RECODE: 5 recoded variablesThese 25 variables were recoded (grouped) into 5 simpler categories for data analysis: No High School Diploma, High School Diploma or GED, Some College, Bachelor's Degree, and Advanced or Professional DegreeSEXGender2 variables1 - Male, 2 - FemaleVALPProperty Value1 variableValues were rounded and top-coded by ACS for anonymity. The "-1" variable is defined as N/A (GQ/ Vacant lots except 'for sale only' and 'sold, not occupied' / not owned or being bought.) This variable reflects the median value of property owned by individuals of each race, ethnicity, gender, and educational attainment category.PUMAPublic Use Microdata Area18 PUMAsPUMAs in New Mexico can be viewed here:https://nmcdc.maps.arcgis.com/apps/mapviewer/index.html?webmap=d9fed35f558948ea9051efe9aa529eafData includes 19 total regions: 18 Pumas and NM State TotalsNOTES AND RESOURCESThe following resources and documentation were used to navigate the ACS PUMS system and to answer questions about variables:Census Microdata API User Guide:https://www.census.gov/data/developers/guidance/microdata-api-user-guide.Additional_Concepts.html#list-tab-1433961450Accessing PUMS Data:https://www.census.gov/programs-surveys/acs/microdata/access.htmlHow to use PUMS on data.census.govhttps://www.census.gov/programs-surveys/acs/microdata/mdat.html2019 PUMS Documentation:https://www.census.gov/programs-surveys/acs/microdata/documentation.2019.html#list-tab-13709392012014 to 2018 ACS PUMS Data Dictionary:https://www2.census.gov/programs-surveys/acs/tech_docs/pums/data_dict/PUMS_Data_Dictionary_2014-2018.pdf2019 PUMS Tiger/Line Shapefileshttps://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2019&layergroup=Public+Use+Microdata+Areas Note 1: NMCDC attemepted to contact analysts with the ACS system to clarify questions about variables, but did not receive a timely response. Documentation was then consulted.Note 2: All relevant documentation was reviewed and seems to imply that all survey questions were answered by adults, age 18 or over. Youth who have inherited property could potentially be reflected in this data.Dataset and feature service created in May 2023 by Renee Haley, Data Specialist, NMCDC.
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The data on relationship to householder were derived from answers to Question 2 in the 2015 American Community Survey (ACS), which was asked of all people in housing units. The question on relationship is essential for classifying the population information on families and other groups. Information about changes in the composition of the American family, from the number of people living alone to the number of children living with only one parent, is essential for planning and carrying out a number of federal programs.
The responses to this question were used to determine the relationships of all persons to the householder, as well as household type (married couple family, nonfamily, etc.). From responses to this question, we were able to determine numbers of related children, own children, unmarried partner households, and multi-generational households. We calculated average household and family size. When relationship was not reported, it was imputed using the age difference between the householder and the person, sex, and marital status.
Household – A household includes all the people who occupy a housing unit. (People not living in households are classified as living in group quarters.) A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live separately from any other people in the building and which have direct access from the outside of the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated people who share living arrangements.
Average Household Size – A measure obtained by dividing the number of people in households by the number of households. In cases where people in households are cross-classified by race or Hispanic origin, people in the household are classified by the race or Hispanic origin of the householder rather than the race or Hispanic origin of each individual.
Average household size is rounded to the nearest hundredth.
Comparability – The relationship categories for the most part can be compared to previous ACS years and to similar data collected in the decennial census, CPS, and SIPP. With the change in 2008 from “In-law” to the two categories of “Parent-in-law” and “Son-in-law or daughter-in-law,” caution should be exercised when comparing data on in-laws from previous years. “In-law” encompassed any type of in-law such as sister-in-law. Combining “Parent-in-law” and “son-in-law or daughter-in-law” does not represent all “in-laws” in 2008.
The same can be said of comparing the three categories of “biological” “step,” and “adopted” child in 2008 to “Child” in previous years. Before 2008, respondents may have considered anyone under 18 as “child” and chosen that category. The ACS includes “foster child” as a category. However, the 2010 Census did not contain this category, and “foster children” were included in the “Other nonrelative” category. Therefore, comparison of “foster child” cannot be made to the 2010 Census. Beginning in 2013, the “spouse” category includes same-sex spouses.
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TwitterOffice for National Statistics' national and subnational Census 2021. ReligionThis dataset provides Census 2021 estimates that classify usual residents in England and Wales by religion. The estimates are as at Census Day, 21 March 2021. Religion definition: The religion people connect or identify with (their religious affiliation), whether or not they practice or have belief in it. This question was voluntary and includes people who identified with one of 8 tick-box response options, including 'No religion', alongside those who chose not to answer this question.Comparability with 2011: Broadly comparable. This derived variable can be generally compared with the same variable used in the 2011 Census, but there are some quality issues in the data This data is issued at (BGC) Generalised (20m) boundary type for:Country - England and WalesRegion - EnglandUTLA - England and WalesLTLA - England and WalesWard - England and WalesMSOA - England and WalesLSOA - England and WalesOA - England and WalesIf you require the data at full resolution boundaries, or if you are interested in the range of statistical data that Esri UK make available in ArcGIS Online please enquire at content@esriuk.com.The data services available from this page are derived from the National Data Service. The NDS delivers thousands of open national statistical indicators for the UK as data-as-a-service. Data are sourced from major providers such as the Office for National Statistics, Public Health England and Police UK and made available for your area at standard geographies such as counties, districts and wards and census output areas. This premium service can be consumed as online web services or on-premise for use throughout the ArcGIS system.Read more about the NDS.
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Context
The dataset tabulates the population of San Patricio County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of San Patricio County across both sexes and to determine which sex constitutes the majority.
Key observations
There is a slight majority of male population, with 50.91% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
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
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.
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/.
This dataset is a part of the main dataset for San Patricio County Population by Gender. You can refer the same here
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This dataset provides Census 2022 estimates for ethnic group by religion in UK in Scotland.
Ethnic group classifies people according to their own perceived ethnic group and cultural background. Whilst the main ethnic group categories have not changed from the question asked in Census 2011, some of the detailed response options and write-in prompts for Scotland's Census 2022 were changed based on stakeholder engagement and subsequent question testing.
Details of classification can be found here
The quality assurance report can be found here
This is a person’s current religious denomination or body that they belong to, or if the person does not have a religion, ‘No Religion’. No determination is made about whether a person was a practising member of a religion.
Religion is a voluntary question and 6.2% of the population did not provide a response. Please be aware that when we state percentages these are out of the whole population, not just those that provided a response. Our approach to imputation is also different for voluntary questions. Not stating a religion is considered to be a valid response, so we do not impute a religion for those who responded to the census but did not answer the religion question. However, we do impute religion for those who did not respond at all to the census. 'Not stated’ is one of the values that can be imputed for religion. More information on our edit and imputation method is available on the Scotland’s Census website.
Classification and comparison with 2011 census can be found here
The quality assurance report can be found here
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This dataset provides Census 2022 estimates for the Religion by Individuals in Scotland.
A person's age on Census Day, 20 March 2022. Infants aged under 1 year are classified as 0 years of age.
This is the sex recorded by the person completing the census. The options were "Female" and "Male". Guidance on answering the question can be found here
This is a person’s current religious denomination or body that they belong to, or if the person does not have a religion, ‘No Religion’. No determination is made about whether a person was a practising member of a religion.
Religion is a voluntary question and 6.2% of the population did not provide a response. Please be aware that when we state percentages these are out of the whole population, not just those that provided a response. Our approach to imputation is also different for voluntary questions. Not stating a religion is considered to be a valid response, so we do not impute a religion for those who responded to the census but did not answer the religion question. However, we do impute religion for those who did not respond at all to the census. 'Not stated’ is one of the values that can be imputed for religion. More information on our edit and imputation method is available on the Scotland’s Census website.
Classification and comparison with 2011 census can be found here
The quality assurance report can be found here
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TwitterThe Participation Survey started in October 2021 and is the key evidence source on engagement for DCMS. It is a continuous push-to-web household survey of adults aged 16 and over in England.
The Participation Survey provides nationally representative estimates of physical and digital engagement with the arts, heritage, museums & galleries, and libraries, as well as engagement with tourism, major events, live sports and digital.
The Participation Survey is only asked of adults in England. Currently there is no harmonised survey or set of questions within the administrations of the UK. Data on participation in cultural sectors for the devolved administrations is available in the https://www.gov.scot/collections/scottish-household-survey/">Scottish Household Survey, https://gov.wales/national-survey-wales">National Survey for Wales and https://www.communities-ni.gov.uk/topics/statistics-and-research/culture-and-heritage-statistics">Northern Ireland Continuous Household Survey.
The pre-release access document above contains a list of ministers and officials who have received privileged early access to this release of Participation Survey data. In line with best practice, the list has been kept to a minimum and those given access for briefing purposes had a maximum of 24 hours. Details on the pre-release access arrangements for this dataset are available in the accompanying material.
Our statistical practice is regulated by the OSR. OSR sets the standards of trustworthiness, quality and value in the https://code.statisticsauthority.gov.uk/the-code/">Code of Practice for Statistics that all producers of official statistics should adhere to.
Patterns were identified in Census 2021 data that suggest that some respondents may not have interpreted the gender identity question as intended, notably those with lower levels of English language proficiency. https://www.scotlandscensus.gov.uk/2022-results/scotland-s-census-2022-sexual-orientation-and-trans-status-or-history/">Analysis of Scotland’s census, where the gender identity question was different, has added weight to this observation. Similar respondent error may have occurred during the data collection for these statistics so comparisons between subnational and other smaller group breakdowns should be considered with caution. More information can be found in the ONS https://www.ons.gov.uk/peoplepopulationandcommunity/culturalidentity/sexuality/methodologies/sexualorientationandgenderidentityqualityinformationforcensus2021">sexual orientation and gender identity quality information report, and in the National Statistical https://blog.ons.gov.uk/2024/09/12/better-understanding-the-strengths-and-limitations-of-gender-identity-statistics/">blog about the strengths and limitations of gender identity statistics.
You are welcome to contact us directly with any comments about how we meet these standards by emailing evidence@dcms.gov.uk. Alternatively, you can contact OSR by emailing regulation@statistics.gov.uk or via the OSR website.
The responsible statisticians for this release are Oliver Maxwell and Alice Louth. For enquiries on this release, contact participationsurvey@dcms.gov.uk.
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TwitterFor more data on Austin demographics please visit austintexas.gov/demographics. This measure answers the question of percentage of people working in Austin that come from outside Austin. The LODES program collects administrative records from unemployment insurance reporting systems. Residence location is derived from annual federal administrative data. LODES are produced and released at the census block level, with all tabulations consisting of paired, origin-destination flows that can also be aggregated to the residence and workplace margins.
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This dataset provides Census 2022 estimates for the Country of Birth by religion in Scotland.
Country of birth is the country in which a person was born. Users should be mindful of changes in EU members and accession states between 2011 and 2022. This will affect the number of countries which make up certain categories when comparing the results between censuses.
Details of classification can be found here
The quality assurance report can be found here
This is a person’s current religious denomination or body that they belong to, or if the person does not have a religion, ‘No Religion’. No determination is made about whether a person was a practising member of a religion.
Religion is a voluntary question and 6.2% of the population did not provide a response. Please be aware that when we state percentages these are out of the whole population, not just those that provided a response. Our approach to imputation is also different for voluntary questions. Not stating a religion is considered to be a valid response, so we do not impute a religion for those who responded to the census but did not answer the religion question. However, we do impute religion for those who did not respond at all to the census. 'Not stated’ is one of the values that can be imputed for religion. More information on our edit and imputation method is available on the Scotland’s Census website.
Classification and comparison with 2011 census can be found here
The quality assurance report can be found here
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TwitterThis is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics. This measure answers the question of percentage of people working in Austin that come from outside Austin. The LODES program collects administrative records from unemployment insurance reporting systems. Residence location is derived from annual federal administrative data. LODES are produced and released at the census block level, with all tabulations consisting of paired, origin-destination flows that can also be aggregated to the residence and workplace margins.
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This dataset provides Census 2021 estimates that classify usual residents in England and Wales by national identity and by religion. The estimates are as at Census Day, 21 March 2021.
The increase since the 2011 Census in people identifying as “British” and fall in people identifying as “English” may partly reflect true changes in self-perception. It is also likely to reflect that “British” replaced “English” as the first response option listed on the questionnaire in England. Read more about this quality notice.
Area type
Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.
For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.
Lower tier local authorities
Lower tier local authorities provide a range of local services. There are 309 lower tier local authorities in England made up of 181 non-metropolitan districts, 59 unitary authorities, 36 metropolitan districts and 33 London boroughs (including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities.
Coverage
Census 2021 statistics are published for the whole of England and Wales. However, you can choose to filter areas by:
National identity
Someone’s national identity is a self-determined assessment of their own identity, it could be the country or countries where they feel they belong or think of as home. It is not dependent on ethnic group or citizenship.
Respondents could select more than one national identity.
Religion
The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it.
This question was voluntary and includes people who identified with one of 8 tick-box response options, including "No religion", alongside those who chose not to answer this question.
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This dataset provides Census 2022 estimates for the Religion by Individuals in Scotland.
This is a person’s current religious denomination or body that they belong to, or if the person does not have a religion, ‘No Religion’. No determination is made about whether a person was a practising member of a religion.
Religion is a voluntary question and 6.2% of the population did not provide a response. Please be aware that when we state percentages these are out of the whole population, not just those that provided a response. Our approach to imputation is also different for voluntary questions. Not stating a religion is considered to be a valid response, so we do not impute a religion for those who responded to the census but did not answer the religion question. However, we do impute religion for those who did not respond at all to the census. 'Not stated’ is one of the values that can be imputed for religion. More information on our edit and imputation method is available on the Scotland’s Census website.
Classification and comparison with 2011 census can be found here
The quality assurance report can be found here
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This dataset provides Census 2021 estimates that classify households with usual residents in England and Wales by various household characteristics, including variations in tenure by household size, household family composition, multi-generational households, and household level information on the age, ethnic group, religion, employment status and occupation of household members. The estimates are as at Census Day, 21 March 2021.
These datasets are part of Household characteristics by tenure, England and Wales: Census 2021, a release of results from the 2021 Census for England and Wales. Figures may differ slightly in future releases because of the impact of removing rounding and applying further statistical processes.
Total counts for some household groups may not match between published tables. This is to protect the confidentiality of households' data. Household counts have been rounded to the nearest 5 and any counts below 10 were suppressed; this is signified by a 'c' in the data tables.
This dataset uses middle layer super output area (MSOA) and lower layer super output area (LSOA) geography boundaries as of 2021 and local authority district geography boundaries as of 2022.
In this dataset, the number of households in an area is broken down by different variables and categories. If you were to sum the counts of households by each variable and category, it may not sum to the total of households in that area. This is because of rounding, suppression and that some tables only include data for certain household groups.
In this dataset, variables may have different categories for different geography levels. When variables are broken down by more categories, they may not sum to the total of the higher level categories due to rounding and suppression.
Social rent is not separated into “housing association, housing co-operative, charitable trust, registered social landlord” and “council or local authority districts” because of respondent error in identifying the type of landlord. This is particularly clear in results for areas which have no local authority districts housing stock, but there are households responding as having a “council or local authority districts” landlord type. Estimates are likely to be accurate when the social rent category is combined.
The Census Quality and Methodology Information report contains important information on:
Quality notes can be found here
Housing quality information for Census 2021 can be found here
Household
A household is defined as one person living alone, or a group of people (not necessarily related) living at the same address who share cooking facilities and a living room, sitting room or dining area. This includes all sheltered accommodation units in an establishment (irrespective of whether there are other communal facilities) and all people living in caravans on any type of site that is their usual residence; this will include anyone who has no other usual residence elsewhere in the UK. A household must contain at least one person whose place of usual residence is at the address. A group of short-term residents living together is not classified as a household, and neither is a group of people at an address where only visitors are staying.
Usual resident
For Census 2021, a usual resident of the UK is anyone who, on Census Day, was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more, or had a permanent UK address and was outside the UK and intended to be outside the UK for less than 12 months.
Household reference person (HRP)
A person who serves as a reference point, mainly based on economic activity and age, to characterize a whole household. The person is not necessarily the member of the household in whose name the accommodation is owned or rented.
Tenure
Whether a household owns or rents the accommodation that it occupies. Owner-occupied accommodation can be: owned outright, which is where the household owns all of the accommodation; owned with a mortgage or loan; or part owned on a shared ownership scheme. Rented accommodation can be private rented, for example, rented through a private landlord or letting agent; social rented through a local council or housing association; or lived in rent free, which is where the household does not own the accommodation and does not pay rent to live there, for example living in a relative or friend’s property or live-in carers or nannies. This information is not available for household spaces with no usual residents.
_Household size _
The number of usual residents in the household.
Household family composition
Households according to the relationships between members. Single-family households are classified by the number of dependent children and family type (married, civil partnership or cohabiting couple family, or lone parent family). Other households are classified by the number of people, the number of dependent children and whether the household consists only of students or only of people aged 66 years and over.
Multi-generational households
Households where people from across more than two generations of the same family live together. This includes households with grandparents and grandchildren whether or not the intervening generation also live in the household.
_Household combination of resident age _
Classifies households by the ages of household members on 21 March 2021. Households could be made up of residents aged 15 years and under; residents aged 16 to 64 years; residents aged 65 years and over; or a combination of these.
Ethnic group
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options. For more information, see ONS's Ethnic group, England and Wales: Census 2021 bulletin
Household combination of resident ethnic group
Classifies households by the ethnic groups household members identified with.
Religion
The religion people connect or identify with (their religious affiliation), whether or not they practice or have belief in it. This question was voluntary and includes people who identified with one of 8 tick-box response options, including 'No religion', alongside those who chose not to answer this question. For more information, see ONS's Religion, England and Wales: Census 2021 bulletin
Household combination of resident religion
Classifies households by the religious affiliation of household members who chose to answer the religion question. The classifications may include residents who did not answer the religion question.
Household combination of resident employment status
Classifies households by the employment status of household members aged 16 years and over between 15 and 21 March 2021. Households could be made up of employed residents (employee or self-employed); unemployed residents (looking for work and could start within two weeks, or waiting to start a job that had been offered and accepted); economically inactive residents (unemployed and had not looked for work between 22 February to 21 March 2021, or could not start work within two weeks); or a combination of these.
Occupation
"Classifies what people aged 16 years and over do as their main job. Their job title or details of activities they do in their job and any supervisory or management responsibilities form this classification. This information is used to code responses to an occupation using the Standard Occupational Classification (SOC) 2020. It classifies people who were in employment between 15 March and 21 March 2021, by the SOC code that represents their current occupation. The lowest level of detail available is the four-digit SOC code which includes all codes in three, two and one digit SOC code levels. Occupation classifications include :
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Dataset population: Persons
National identity
A person's national identity is a self-determined assessment of their own identity with respect to the country or countries with which they feel an affiliation. This assessment of identity is not dependent on legal nationality or ethnic group.
The national identity question included six tick box responses:
Where a person ticked 'Other' they were asked to write in the name of the country. People were asked to tick all options that they felt applied to them. This means that in results relating to national identity people may be classified with a single national identity or a combination of identities.
Religion
This is a person's current religion, or if the person does not have a religion, 'No religion'. No determination is made about whether a person was a practicing member of a religion. Unlike other census questions where missing answers are imputed, this question was voluntary and where no answer was provided, the response is categorised as 'Not stated'.
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This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group and by religion. The estimates are as at Census Day, 21 March 2021.
Area type
Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.
For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.
Lower tier local authorities
Lower tier local authorities provide a range of local services. There are 309 lower tier local authorities in England made up of 181 non-metropolitan districts, 59 unitary authorities, 36 metropolitan districts and 33 London boroughs (including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities.
Coverage
Census 2021 statistics are published for the whole of England and Wales. However, you can choose to filter areas by:
Ethnic group
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance.
Respondents could choose one out of 19 tick-box response categories, including write-in response options.
Religion
The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it.
This question was voluntary and includes people who identified with one of 8 tick-box response options, including "No religion", alongside those who chose not to answer this question.
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This dataset provides Census 2021 estimates that classify Household Reference Persons in England and Wales by whether residents have identified with one or multiple religions in a household, by ethnic group. The estimates are as at Census Day, 21 March 2021.
Area type
Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.
For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.
Lower tier local authorities
Lower tier local authorities provide a range of local services. There are 309 lower tier local authorities in England made up of 181 non-metropolitan districts, 59 unitary authorities, 36 metropolitan districts and 33 London boroughs (including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities.
Coverage
Census 2021 statistics are published for the whole of England and Wales. However, you can choose to filter areas by:
Multiple religions in household
Classifies households by whether members identify with the same religion, no religion, did not answer the question, or a combination of these options.
This question was voluntary and the variable includes those who answered the question alongside those who chose not to.
Ethnic group
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance.
Respondents could choose one out of 19 tick-box response categories, including write-in response options.
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This dataset is an analysis of the Characteristics of usual residents by whether they have previously served in the UK armed forces, with adjusted estimates for the non-veteran population, based on Census 2021.
People who have previously served in the UK armed forces includes those who have served for at least one day in HM’s Armed Forces, either regular or reserves, or Merchant Mariners who have seen duty on legally defined military operations. It does not include those who have left and since re-entered the regular or reserve UK armed forces, those who have only served in.
The veteran population are older than the general population and also differ in relation to sex and where they live, and these factors interact with other personal characteristics. For example, age can be strongly related to other personal characteristics such as legal partnership status, health and religion. Because of this, veterans may also differ to the usual or non-veteran population when considering related factors such as health and legal partnership status. It is important to be aware of these differences but also to understand when these differences are not attributable to experience of having previously served in the UK armed forces.
Country of birth
The country in which a person was born. For people not born in one of in the four parts of the UK, there was an option to select "elsewhere". People who selected "elsewhere" were asked to write in the current name for their country of birth.
Ethnic group and high-level ethnic group
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options. High-level ethnic group refers to the first stage of the two-stage ethnic group question. High-level groups refer to the first stage where the respondent identifies through one of the following options: * "Asian, Asian British, Asian Welsh" * "Black, Black British, Black Welsh, Caribbean or African" * "Mixed or Multiple" * "White" * "Other ethnic group"
General health
A person's assessment of the general state of their health from very good to very bad. This assessment is not based on a person's health over any specified period of time.
Legal partnership status
Classifies a person according to their legal marital or registered civil partnership status on Census Day 21 March 2021.
Gender identity
Gender identity refers to a person’s sense of their own gender, whether male, female or another category such as non-binary. This may or may not be the same as their sex registered at birth.
Religion
The religion people connect or identify with (their religious affiliation), whether or not they practice or have belief in it. This question was voluntary, and the variable includes people who answered the question, including “No religion”, alongside those who chose not to answer this question. This variable classifies responses into the eight tick-box response options. Write-in responses are classified by their "parent" religious affiliation, including “No religion”, where applicable.
Sexual orientation
Sexual orientation is an umbrella term covering sexual identity, attraction, and behaviour. For an individual respondent, these may not be the same. For example, someone in an opposite-sex relationship may also experience same-sex attraction, and vice versa. This means the statistics should be interpreted purely as showing how people responded to the question, rather than being about whom they are attracted to or their actual relationships. We have not provided glossary entries for individual sexual orientation categories. This is because individual respondents may have differing perspectives on the exact meaning.
Usual resident
A usual resident is anyone who on Census Day, 21 March 2021, was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more, or had a permanent UK address and was outside the UK and intended to be outside the UK for less than 12 months.
UK armed forces veteran
People who have previously served in the UK armed forces. This includes those who have served for at least one day in HM’s Armed Forces, either regular or reserves, or Merchant Mariners who have seen duty on legally defined military operations. It does not include those who have left and since re-entered the regular or reserve UK armed forces, those who have only served in foreign armed forces, or those who have served in the UK armed forces and are currently living outside of England and Wales.
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This dataset is an analysis of the Characteristics by previous service as a regular or reserve in the UK armed forces from Census 2021.
People who have previously served in the UK armed forces includes those who have served for at least one day in HM’s Armed Forces, either regular or reserves, or Merchant Mariners who have seen duty on legally defined military operations. It does not include those who have left and since re-entered the regular or reserve UK armed forces, those who have only served in.
Country of birth
The country in which a person was born. For people not born in one of in the four parts of the UK, there was an option to select "elsewhere". People who selected "elsewhere" were asked to write in the current name for their country of birth.
Ethnic group and high-level ethnic group
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options. High-level ethnic group refers to the first stage of the two-stage ethnic group question. High-level groups refer to the first stage where the respondent identifies through one of the following options: * "Asian, Asian British, Asian Welsh" * "Black, Black British, Black Welsh, Caribbean or African" * "Mixed or Multiple" * "White" * "Other ethnic group"
General health
A person's assessment of the general state of their health from very good to very bad. This assessment is not based on a person's health over any specified period of time.
Legal partnership status
Classifies a person according to their legal marital or registered civil partnership status on Census Day 21 March 2021.
Religion
The religion people connect or identify with (their religious affiliation), whether or not they practice or have belief in it. This question was voluntary, and the variable includes people who answered the question, including “No religion”, alongside those who chose not to answer this question. This variable classifies responses into the eight tick-box response options. Write-in responses are classified by their "parent" religious affiliation, including “No religion”, where applicable.
Usual resident
A usual resident is anyone who on Census Day, 21 March 2021, was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more, or had a permanent UK address and was outside the UK and intended to be outside the UK for less than 12 months.
UK armed forces veteran
People who have previously served in the UK armed forces. This includes those who have served for at least one day in HM’s Armed Forces, either regular or reserves, or Merchant Mariners who have seen duty on legally defined military operations. It does not include those who have left and since re-entered the regular or reserve UK armed forces, those who have only served in foreign armed forces, or those who have served in the UK armed forces and are currently living outside of England and Wales.
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TwitterA detailed explanation of how this dataset was put together, including data sources and methodologies, follows below.Please see the "Terms of Use" section below for the Data DictionaryDATA ACQUISITION AND CLEANING PROCESSThis dataset was built from 5 separate datasets queried during the months of April and May 2023 from the Census Microdata System (link below):https://data.census.gov/mdat/#/All datasets include information on Property Value (VALP) by: Educational Attainment (SCHL), Gender (SEX), a specified race or ethnicity (RAC or HISP), and are grouped by Public Use Microdata Areas (PUMAS). PUMAS are geographic areas created by the Census bureau; they are weighted by land area and population to facilitate data analysis. Data also Included totals for the state of New Mexico, so 19 total geographies are represented. Datasets were downloaded separately by race and ethnicity because this was the only way to obtain the VALP, SCHL, and SEX variables intersectionally with race or ethnicity data. Datasets were downloaded separately by race and ethnicity because this was the only way to obtain the VALP, SCHL, and SEX variables intersectionally with race or ethnicity data. Cleaning each dataset started with recoding the SCHL and HISP variables - details on recoding can be found below.After recoding, each dataset was transposed so that PUMAS were rows and SCHL, VALP, SEX, and Race or Ethnicity variables were the columns.Median values were calculated in every case that recoding was necessary. As a result, all Property Values in this dataset reflect median values.At times the ACS data downloaded with zeros instead of the 'null' values in initial query results. The VALP variable also included a "-1" variable to reflect N/A values (details in variable notes). Both zeros and "-1" values were removed before calculating median values, both to keep the data true to the original query and to generate accurate median values.Recoding the SCHL variable resulted in 5 rows for each PUMA, reflecting the different levels of educational attainment in each region. Columns grouped variables by race or ethnicity and gender. Cell values were property values.All 5 datasets were joined after recoding and cleaning the data. Original datasets all include 95 rows with 5 separate Educational Attainment variables for each PUMA, including New Mexico State totals.Because 1 row was needed for each PUMA in order to map this data, the data was split by Educational Attainment (SCHL), resulting in 110 columns reflecting median property values for each race or ethnicity by gender and level of educational attainment.A short, unique 2 to 5 letter alias was created for each PUMA area in anticipation of needing a unique identifier to join the data with. GIS AND MAPPING PROCESSA PUMA shapefile was downloaded from the ACS site. The Shapefile can be downloaded here: https://tigerweb.geo.census.gov/arcgis/rest/services/TIGERweb/PUMA_TAD_TAZ_UGA_ZCTA/MapServerThe DBF from the PUMA shapefile was exported to Excel; this shapefile data included needed geographic information for mapping such as: GEOID, PUMACE. The UIDs created for each PUMA were added to the shapefile data; the PUMA shapfile data and ACS data were then joined on UID in JMP.The data table was joined to the shapefile in ARC GiIS, based on PUMA region (specifically GEOID text).The resulting shapefile was exported as a GDB (geodatabase) in order to keep 'Null' values in the data. GDBs are capable of including a rule allowing null values where shapefiles are not. This GDB was uploaded to NMCDCs Arc Gis platform. SYSTEMS USEDMS Excel was used for data cleaning, recoding, and deriving values. Recoding was done directly in the Microdata system when possible - but because the system is was in beta at the time of use some features were not functional at times.JMP was used to transpose, join, and split data. ARC GIS Desktop was used to create the shapefile uploaded to NMCDC's online platform. VARIABLE AND RECODING NOTESTIMEFRAME: Data was queried for the 5 year period of 2015 to 2019 because ACS changed its definiton for and methods of collecting data on race and ethinicity in 2020. The change resulted in greater aggregation and les granular data on variables from 2020 onward.Note: All Race Data reflects that respondants identified as the specified race alone or in combination with one or more other races.VARIABLE:ACS VARIABLE DEFINITIONACS VARIABLE NOTESDETAILS OR URL FOR RAW DATA DOWNLOADRACBLKBlack or African American ACS Query: RACBLK, SCHL, SEX, VALP 2019 5yrRACAIANAmerican Indian and Alaska Native ACS Query: RACAIAN, SCHL, SEX, VALP 2019 5yrRACASNAsian ACS Query: RACASN, SCHL, SEX, VALP 2019 5yrRACWHTWhite ACS Query: RACWHT, SCHL, SEX, VALP 2019 5yrHISPHispanic Origin ACS Query: HISP ORG, SCHL, SEX, VALP 2019 5yrHISP RECODE: 24 original separate variablesThe Hispanic Origin (HISP) variable originally included 24 subcategories reflecting Mexican, Central American, South American, and Caribbean Latino, and Spanish identities from each Latin American counry. 7 recoded VariablesThese 24 variables were recoded (grouped) into 7 simpler categories for data analysis: Not Spanish/Hispanic/Latino, Mexican, Caribbean Latino, Central American, South American, Spaniard, All other Spanish/Hispanic/Latino Female. Not Spanish/Hispanic/Latino was not really used in the final dataset as the race datasets provided that information.SCHLEducational Attainment25 original separate variablesThe Educational Attainment (SCHL) variable originally included 25 subcategories reflecting the education levels of adults (over 18) surveyed by the ACS. These include: Kindergarten, Grades 1 through 12 separately, 12th grade with no diploma, Highschool Diploma, GED or credential, less than 1 year of college, more than 1 year of college with no degree, Associate's Degree, Bachelor's Degree, Master's Degree, Professional Degree, and Doctorate Degree.SCHL RECODE: 5 recoded variablesThese 25 variables were recoded (grouped) into 5 simpler categories for data analysis: No High School Diploma, High School Diploma or GED, Some College, Bachelor's Degree, and Advanced or Professional DegreeSEXGender2 variables1 - Male, 2 - FemaleVALPProperty Value1 variableValues were rounded and top-coded by ACS for anonymity. The "-1" variable is defined as N/A (GQ/ Vacant lots except 'for sale only' and 'sold, not occupied' / not owned or being bought.) This variable reflects the median value of property owned by individuals of each race, ethnicity, gender, and educational attainment category.PUMAPublic Use Microdata Area18 PUMAsPUMAs in New Mexico can be viewed here:https://nmcdc.maps.arcgis.com/apps/mapviewer/index.html?webmap=d9fed35f558948ea9051efe9aa529eafData includes 19 total regions: 18 Pumas and NM State TotalsNOTES AND RESOURCESThe following resources and documentation were used to navigate the ACS PUMS system and to answer questions about variables:Census Microdata API User Guide:https://www.census.gov/data/developers/guidance/microdata-api-user-guide.Additional_Concepts.html#list-tab-1433961450Accessing PUMS Data:https://www.census.gov/programs-surveys/acs/microdata/access.htmlHow to use PUMS on data.census.govhttps://www.census.gov/programs-surveys/acs/microdata/mdat.html2019 PUMS Documentation:https://www.census.gov/programs-surveys/acs/microdata/documentation.2019.html#list-tab-13709392012014 to 2018 ACS PUMS Data Dictionary:https://www2.census.gov/programs-surveys/acs/tech_docs/pums/data_dict/PUMS_Data_Dictionary_2014-2018.pdf2019 PUMS Tiger/Line Shapefileshttps://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2019&layergroup=Public+Use+Microdata+Areas Note 1: NMCDC attemepted to contact analysts with the ACS system to clarify questions about variables, but did not receive a timely response. Documentation was then consulted.Note 2: All relevant documentation was reviewed and seems to imply that all survey questions were answered by adults, age 18 or over. Youth who have inherited property could potentially be reflected in this data.Dataset and feature service created in May 2023 by Renee Haley, Data Specialist, NMCDC.