9 datasets found
  1. S

    South Africa Population: 15 to 64 Years: White

    • ceicdata.com
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    CEICdata.com, South Africa Population: 15 to 64 Years: White [Dataset]. https://www.ceicdata.com/en/south-africa/population/population-15-to-64-years-white
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 1, 2015 - Mar 1, 2018
    Area covered
    South Africa
    Variables measured
    Population
    Description

    South Africa Population: 15 to 64 Years: White data was reported at 2,978.591 Person th in Sep 2018. This records a decrease from the previous number of 2,987.055 Person th for Jun 2018. South Africa Population: 15 to 64 Years: White data is updated quarterly, averaging 3,143.298 Person th from Mar 2008 (Median) to Sep 2018, with 43 observations. The data reached an all-time high of 3,277.317 Person th in Mar 2008 and a record low of 2,978.591 Person th in Sep 2018. South Africa Population: 15 to 64 Years: White data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G001: Population.

  2. Population Census 1985 - South Africa

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Mar 29, 2019
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    Statistics South Africa (2019). Population Census 1985 - South Africa [Dataset]. https://catalog.ihsn.org/catalog/2865
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    Statistics South Africahttp://www.statssa.gov.za/
    Time period covered
    1985
    Area covered
    South Africa
    Description

    Geographic coverage

    The 1985 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

    The 1985 Census dataset contains 9 data files. These refer to Development Regions demarcated by the South African Government according to their socio-economic conditions and development needs. These Development Regions are labeled A to J (there is no Region I, presumably because Statistics SA felt an "I" could be confused with the number 1). The 9 data files in the 1985 Census dataset refer to the following areas:

    DEV REGION AREA COVERED A Western Cape Province including Walvis Bay B Northern Cape C Orange Free State and Qwaqwa D Eastern Cape/Border E Natal and Kwazulu F Eastern Transvaal, KaNgwane and part of the Simdlangentsha district of Kwazulu G Northern Transvaal, Lebowa and Gazankulu H PWV area, Moutse and KwaNdebele J Western Transvaal

    Analysis unit

    The units of analysis under observation in the South African census 1985 are households and individuals

    Universe

    The South African census 1985 census covered the provinces of the Cape, the Orange Free State, Transvaal, and Nata and the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    Although the census was meant to cover all residents of the so called white areas of South Africa, in 88 areas door-to-door surveys were not possible and the population in these areas was enumerated by means of a sample survey conducted by the Human Sciences Research Council.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The1985 population census questionnaire was administered to each household and collected information on household and area type, and information on household members, including relationship within household, sex, age, marital status, population group, birthplace, country of citizenship, level of education, occupation, identity of employer and the nature of economic activities

    Data appraisal

    UNDER-ENUMERATION: The following under-enumeration figures have been calculated for the 1985 census. Estimated percentage distribution of undercount by race according to the HSRC: Percent undercount
    Whites 7.6%
    Blacks in the “RSA” 20.4% Blacks in the “National States” 15.1% Coloureds 1.0% Asians 4.6%

  3. Population Census 1980 - South Africa

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated May 1, 2014
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    Statistics South Africa (2014). Population Census 1980 - South Africa [Dataset]. https://microdata.worldbank.org/index.php/catalog/909
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    Dataset updated
    May 1, 2014
    Dataset authored and provided by
    Statistics South Africahttp://www.statssa.gov.za/
    Time period covered
    1980
    Area covered
    South Africa
    Description

    Abstract

    The 1980 South African Population Census was a count of all persons present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980). The purpose of the population census was to collect, process and disseminate detailed statistics on population size, composition and distribution at small area level. The 1980 South African Population Census contains data collected on HOUSEHOLDS: household goods and dwelling characteristics as well as employment of domestic workers; INDIVIDUALS: population group, citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities

    Geographic coverage

    The 1980 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered areas in the following so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, and Kwandebele. The 1980 South African census excluded the areas of the Transkei and Bophuthatswana. A census data file for Bophuthatswana was released with the final South African Census 1980 dataset.

    Analysis unit

    The units of analysis of the 1980 census includes households, individuals and institutions

    Universe

    The 1980 South African census covered all household members (usual residents).

    The 1980 South African Population Census was enumerated on a de facto basis, that is, according to the place where persons were located during the census. All persons who were present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980) were enumerated and included in the data. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active, were not enumerated and included in the figures. Likewise, members of the Diplomatic and Consular Corps of foreign countries were not included. However, the South African personnel linked to the foreign missions including domestic workers were enumerated. Crews and passengers of ships were also not enumerated, unless they were normally resident in the Republic of South Africa. Residents of the RSA who were absent from the night were as far as possible enumerated on their return and included in the region where they normally resided. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria).

    Kind of data

    Census/enumeration data [cen]

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The 1980 Population Census questionnaire was administered to all household members and covered household goods and dwelling characteristics, and employment of domestic workers. Questions concerning individuals included those on citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities.

    The following questions appear in the questionnaire but the corresponding data has not been included in the data set: PART C: PARTICULARS OF DWELLING: 2. How many separate families (i) Number of families (ii) Number of non-family persons (iii) total number of occupants [i.e. persons in families shown against (i) plus persons shown against 3. Persons employed by household Full-time, Part-time (a) How many persons are employed as domestics by you? (Include garden workers) (b) Total cash wages paid to above –mentioned persons for April 1980 4. Ownership – Do not answer this question if your dwelling is on a farm. (i) Own dwelling – (Including hire-purchase, sectional title property or property of wife): (a) Is the dwelling Fully paid Partly paid-off (b) If partly paid-off, state monthly repayment (include housing subsidy, but exclude insurance. (ii) Rented or occupied free dwelling : (a) Is the dwelling occupied free, rented furnished, rented unfurnished (b) If rented, state monthly rent (c) Is the dwelling owned by the employer? (d) Does it belong to the state, SA Railways, a provincial administration, a divisional council, or a municipality or other local authority? PART D: PARTICULARS OF THE FAMILY 1. Number of members in the family 2. Occupation. (Nature of work done) (a) Head of family (b) Wife 3. Annual income of head of family and wife. Annual income of: Head, Wife (if applicable)

  4. w

    Scoping review on living conditions in Johannesburg, South Africa during...

    • opendata.wits.ac.za
    docx
    Updated Mar 12, 2025
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    Keith Beavon (2025). Scoping review on living conditions in Johannesburg, South Africa during apartheid regime [Dataset]. http://doi.org/10.71796/wits-figshare.27923643.v1
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    docxAvailable download formats
    Dataset updated
    Mar 12, 2025
    Dataset provided by
    University of the Witwatersrand, Johannesburg
    Authors
    Keith Beavon
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Johannesburg, South Africa
    Description

    This dataset is a collation of articles written by different authors on the history of South Africa during the apartheid regime (1948 to 1994). Apartheid in South Africa was the racial segregation under the all-white government of South Africa which dictated that non-white South Africans (a majority of the population) were required to live in separate areas from whites and use separate public facilities and contact between the two groups would be limited. The different racial group were physically separated according to their location, public facilities and social life.

  5. V

    Loudoun County 2020 Census Population Patterns by Race and Hispanic or...

    • data.virginia.gov
    • datasets.ai
    • +2more
    Updated Nov 13, 2025
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    Loudoun County (2025). Loudoun County 2020 Census Population Patterns by Race and Hispanic or Latino Ethnicity [Dataset]. https://data.virginia.gov/dataset/loudoun-county-2020-census-population-patterns-by-race-and-hispanic-or-latino-ethnicity
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    arcgis geoservices rest api, htmlAvailable download formats
    Dataset updated
    Nov 13, 2025
    Dataset provided by
    Loudoun County GIS
    Authors
    Loudoun County
    Area covered
    Loudoun County
    Description

    Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File.


    Definitions: Definitions of the Census Bureau’s categories are provided below. This interactive map shows patterns for all categories except American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander. The total population countywide for these two categories is small (1,582 and 263 respectively). The Census Bureau uses the following race categories:

    Population by Race

    White – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.

    Black or African American – A person having origins in any of the Black racial groups of Africa.

    American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.

    Asian – A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.

    Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.

    Some Other Race - this category is chosen by people who do not identify with any of the categories listed above.

    People can identify with more than one race. These people are included in the Two or More Races

    Hispanic or Latino Population
    The Hispanic/Latino population is an ethnic group. Hispanic/Latino people may be of any race.


    Other layers provided in this tool included the Loudoun County Census block groups, towns and Dulles airport, and the Loudoun County 2021 aerial imagery.

  6. r

    NESP MaC Project 5.7 - Updating knowledge of Australian white sharks

    • researchdata.edu.au
    Updated Jun 23, 2025
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    Australian Ocean Data Network (2025). NESP MaC Project 5.7 - Updating knowledge of Australian white sharks [Dataset]. https://researchdata.edu.au/nesp-mac-project-white-sharks/3719011
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    Dataset updated
    Jun 23, 2025
    Dataset provided by
    data.gov.au
    Authors
    Australian Ocean Data Network
    Area covered
    Australia
    Description

    This record provides an overview of the NESP Marine and Coastal Hub project "Updating knowledge of Australian white sharks". For specific data outputs from this project, please see child records associated with this metadata. The white shark is listed as vulnerable and migratory under Australia’s Environment Protection and Biodiversity Conservation Act 1999. The national White Shark Recovery Plan 2013 sets out research and management actions necessary to support the recovery of the white shark in Australian waters. Previous research funded by the National Environmental Science Program (NESP) provided updated estimates of white shark breeding population size and trend. However, the results were based on modest data sets and were limited by some critical knowledge gaps in relation to pupping and juvenile nursery areas, and uncertainty about how populations are connected between eastern and south-western Australia. Recent unpublished work has raised the prospect of a single Australian population. The White Shark Recovery Plan 2013 has identified a critical need for a quantitative assessment of population trends and evidence of any recovery of the white shark in Australian waters. This project will provide an update and reduce uncertainty regarding the status, trends, and population structure of white sharks in Australian waters. Specifically, it will focus efforts to identify critical habitats and biologically important areas for white sharks and improve the understanding of population status through advancing close-kin mark recapture research. Three project sub-components will involve: • Investigating the feasibility of filling knowledge gaps about juvenile and pupping areas and adult movements; • Investigating population structure to resolve mixing/connectivity questions; and • Updating population estimates based on significant new data. The project approach will comprise of: (1) A pilot study to assess the effectiveness of tagging adult females (>4.5 metres) and juveniles (>2 m) throughout the southern-western white shark range. Genetic samples will be gathered from around Australia and sought from South Africa and New Zealand to conduct a comprehensive update of white shark stock structure. (2) Using an expanded tissue sample set from New South Wales (~1000 samples) to update and refine estimates of adult population size and population trend for the eastern white shark population. Juvenile numbers will be estimated using data from the New South Wales shark management program. Additional samples from South Australia and Western Australia will be combined with previous samples in the southern-western population to refine estimates of population size. (3) Population estimates undertaken using close-kin mark-recapture, a technique that combines advanced genetics and statistical modelling to infer population demographics by identifying close-kin-pairs (parent-offspring or half-siblings) among a collection of sampled animals. Outputs • New genetic samples and sequencing data for white sharks [dataset] • Tracking data derived from 12 PAT tags [dataset] • Final technical report (including recommendations for systematic future research to assist in identifying additional critical habitat for the south-western white shark population) [written]

  7. u

    Cape Area Panel Study 2002-2009, Waves 1-5 Secure Data - South Africa

    • datafirst.uct.ac.za
    Updated Jul 28, 2020
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    University of Cape Town (2020). Cape Area Panel Study 2002-2009, Waves 1-5 Secure Data - South Africa [Dataset]. http://www.datafirst.uct.ac.za/Dataportal/index.php/catalog/537
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    Dataset updated
    Jul 28, 2020
    Dataset provided by
    University of Cape Town
    University of Michigan
    Time period covered
    2002 - 2009
    Area covered
    South Africa
    Description

    Abstract

    The Cape Area Panel Study (CAPS) is a longitudinal study of the lives of youths in metropolitan Cape Town, South Africa. The first wave of the study collected interviews from about 4800 randomly selected young people age 14-22 in August-December, 2002. Wave 1 also collected information on all members of these young people’s households, as well as a random sample of households that did not have members age 14-22. A third of the youth sample was re-interviewed in 2003 (Wave 2a) and the remaining two thirds were re-visited in 2004 (Wave 2b). The full youth sample was then re-interviewed in 2005 (Wave 3), 2006 (Wave 4) and 2009 (Wave 5). Wave 3 includes interviews with approximately 2000 co-resident parents of young adults, while wave 4 also includes interviews with a sample of older adults (all individuals from the original 2002 households who were born on or before 1 January 1956) and all children born to the female young adults. The fifth wave comprises all respondents interviewed in any of the Waves 2a, 3 or 4. In 2010 there were telephonic follow-ups or proxy interviewed that tried to capture those that were not successfully interviewed during the course of the 2009 fieldwork. The study covers a wide range of outcomes, including schooling, employment, health, family formation, and intergenerational support systems. CAPS began in 2002 as a collaborative project of the Population Studies Center in the Institute for Social Research at the University of Michigan and the Centre for Social Science Research at the University of Cape Town (UCT). Other units involved in subsequent waves include UCT’s Southern African Labour and Development Research Unit and the Research Program in Development Studies at Princeton University.

    The secure version of CAPS 2002-2009 includes date of birth, location (ea number, placename), job and school names and locations, as well as variables used in the processing of the data. The secure version does not include information available in the public release dataset and researchers will have to merge these data with the publicly available data when doing their analyses.

    Geographic coverage

    The survey covered Metropolitan Cape Town.

    Analysis unit

    The unit of analysis for this survey is individuals.

    Universe

    The survey covered youths in Metropolitan Cape Town, South Africa.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The CAPS household sample was drawn through a two-stage process. First, the 'enumeration areas' (EAs) used for the 1996 Population Census were divided into three strata according to whether the population of each was predominantly African, predominantly coloured or predominantly white. A sample of primary sampling units (PSUs) was selected within each stratum with probability proportional to size. Within each PSU a sample of 25 screener households was drawn. The Overview and Technical Documentation for Waves 1-2-3-4-5 provides a more detailed discussion of the sampling design. Data users should take the stratification and clustering into account for all analyses. Strata and PSUs are identified by the majpop and cluster variables respectively.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    • Wave 1 (2002) included a household questionnaire, a young adult questionnaire and a literacy and numeracy evaluation questionnaire
    • Wave 2a (2003) and 2b (2004) both included young adult questionnaires only • Wave 3 (2005) included a household questionnaire, a parent questionnaire and a young adult questionnaire
    • Wave 4 (2006) included a household questionnaire, an older adult questionnaire, a young adult questionnaire, a young adult proxy questionnaire and a child questionnaire
    • Wave 5 (2009) included a young adult questionnaire, young adult telephonic questionnaire and a young adult proxy questionnaire

    The questionaires and technical documentation for use with the secure version of CAPS 2002-2009 should be downloaded from the link to the public access dataset.

    Response rate

    Response rates for the survey are covered in Section 5 on non-response and attrition in the document "The Cape Area Panel Study: Overview and technical documentation: Waves 1-2-3-4-5 (2002-2009)."

  8. g

    Survey of Truth and Reconciliation in South Africa, 2000-2001 - Version 1

    • search.gesis.org
    Updated Oct 15, 2004
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    Gibson, James L. (2004). Survey of Truth and Reconciliation in South Africa, 2000-2001 - Version 1 [Dataset]. http://doi.org/10.3886/ICPSR04030.v1
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    Dataset updated
    Oct 15, 2004
    Dataset provided by
    GESIS search
    ICPSR - Interuniversity Consortium for Political and Social Research
    Authors
    Gibson, James L.
    License

    https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de437672https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de437672

    Area covered
    South Africa
    Description

    Abstract (en): The purpose of this study was to explore the relationship between truth acceptance and reconciliation among South Africans during and since the political transition from Apartheid to democracy. The study investigated the extent to which South Africans participated in the truth as promulgated by the Truth and Reconciliation Commission and the degree to which they were "reconciled." The Truth and Reconciliation Commission (TRC) was based on the Promotion of National Unity and Reconciliation Act of 1995. The TRC investigated past gross human rights violations and granted amnesty to individuals in exchange for full and public disclosure of information related to these crimes. The hypothesis that truth acceptance leads to reconciliation was tested in this research. Data were collected through a rigorous and systematic survey of South Africans. Nearly all relevant segments of the South African population were included in the sample, as well as representative subsamples of at least 250 respondents of most major racial/ethnic/linguistic groups. Questions about the TRC investigated respondent awareness, knowledge, and approval of the activities of the TRC. Respondents were asked for their opinions on the effectiveness of the TRC in its efforts to provide a true and unbiased account of South Africa's history and in awarding compensation to those who suffered abuses under the Apartheid regime. Other questions about the TRC asked respondents how important it was to find out the truth about the past and achieve racial reconciliation. Demographic variables include age, marital status, education level, and employment status. Response Rates: A total of 3,727 interviews were completed. In the primary sample, 3,139 interviews were completed. The boost sample included 588 completed interviews. The overall response rate for the survey was approximately 87 percent. South African population, aged 18 and over. The area probability sample included a primary sample of South Africans of all races and a boost sample of white South Africans. Representative subsamples of at least 250 respondents of most major racial, ethnic, and linguistic groups were also included. 2005-12-15 On 2005-08-15 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-12-15 to reflect these additions. Funding insitution(s): National Science Foundation (SES 9906576). (1) This study was conducted in collaboration with Amanda Gouws (Stellenbosch University, South Africa), Charles Villa-Vicencio (Institute for Justice and Reconciliation, Cape Town, South Africa), and Helen Macdonald (Institute for Justice and Reconciliation, Cape Town, South Africa).(2) Two weight variables are included in the dataset. One weight variable (NATWT) should be used when analysis is not conducted by race, and the other (RACEWT) should be used when conducting analyses comparing respondent race. (3) Users must cite the original NSF grant number in all materials produced from this project.

  9. d

    South African National Health and Nutrition Examination Survey (SANHANES-1)...

    • demo-b2find.dkrz.de
    Updated Sep 20, 2025
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    (2025). South African National Health and Nutrition Examination Survey (SANHANES-1) 2011-12: Adult - All provinces - Dataset - B2FIND [Dataset]. http://demo-b2find.dkrz.de/dataset/c96e2b04-a262-5ab7-b71b-0ec338536612
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    Dataset updated
    Sep 20, 2025
    Area covered
    South Africa
    Description

    The knowledge, attitudes and behaviour of South Africans with respect to NCDs and tuberculosis; The nutritional status of South Africans as it relates to food security, dietary intake/ behaviour including alcohol consumption, body image and weight management; The perceptions of general and mental health (stress and trauma) and the utilisation of healthcare services; The behavioural (smoking, diet, physical inactivity) and social determinants of health and nutrition (demographic, socio-economic status and locality) and relate these to the health and nutritional status of the population. Clinical measurements Face-to-face interview Physical measurements Psychological measurements National; The SANHANES-1 included individuals of all ages living in South Africa. All persons living in occupied households (HHs) were eligible to participate. The survey applied a multi-stage disproportionate, stratified cluster sampling approach. A total of 1 000 census enumeration areas1 (EAs) from the 2001 population census were selected from a database of 86 000 EAs and mapped in 2007 using aerial photography to create the 2007 HSRC master sample to use as a basis for sampling of households. The selection of EAs was stratified by province and locality type. In the formal urban areas, race was also used as a third stratification variable (based on the predominant race group in the selected EA at the time of the 2001 census). The allocation of EAs to different stratification categories was disproportionate, in other words, over-sampling or over-allocation of EAs occurred in areas that were dominated by Indian, coloured or white race groups to ensure that the minimum required sample size in those smaller race groups were obtained. Based on the HSRC 2007 Master Sample, 500 EAs representative of the socio-demographic profile of South Africa were identified and a random sample of 20 visiting points (VPs) were randomly selected from each EA, yielding an overall sample of 10 000. EAs were sampled with probability proportional to the size of the EA using the 2001 census estimate of the number of VPs in the EA database as a measure of size (MOS). 1 An enumeration area (EA) is the spatial area that is used by Statistics South Africa (Stats SA) to collect census information on the South African population. An enumeration area consists of approximately 180 households in urban areas, and 80 to 120 households in rural areas.

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    Learn how you can add new datasets to our index.

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CEICdata.com, South Africa Population: 15 to 64 Years: White [Dataset]. https://www.ceicdata.com/en/south-africa/population/population-15-to-64-years-white

South Africa Population: 15 to 64 Years: White

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Dataset provided by
CEICdata.com
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jun 1, 2015 - Mar 1, 2018
Area covered
South Africa
Variables measured
Population
Description

South Africa Population: 15 to 64 Years: White data was reported at 2,978.591 Person th in Sep 2018. This records a decrease from the previous number of 2,987.055 Person th for Jun 2018. South Africa Population: 15 to 64 Years: White data is updated quarterly, averaging 3,143.298 Person th from Mar 2008 (Median) to Sep 2018, with 43 observations. The data reached an all-time high of 3,277.317 Person th in Mar 2008 and a record low of 2,978.591 Person th in Sep 2018. South Africa Population: 15 to 64 Years: White data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G001: Population.

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