15 datasets found
  1. Distribution of languages spoken inside and outside of households South...

    • statista.com
    Updated Jun 3, 2025
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    Statista (2025). Distribution of languages spoken inside and outside of households South Africa 2018 [Dataset]. https://www.statista.com/statistics/1114302/distribution-of-languages-spoken-inside-and-outside-of-households-in-south-africa/
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    Dataset updated
    Jun 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2018
    Area covered
    South Africa
    Description

    As of 2018, the languages most commonly spoken by individuals inside of South African households were isiZulu at 25.3 percent, isiXhosa at 14.8 percent and Afrikaans at 12.2 percent respectively. While English only accounts for the sixth most common language spoken inside of South African households at 8.1 percent, it is the second-most prevalent language spoken outside of homes, at 16.6 percent.

  2. Number of languages spoken in Africa 2022, by country

    • statista.com
    Updated Jun 30, 2024
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    Statista (2024). Number of languages spoken in Africa 2022, by country [Dataset]. https://www.statista.com/statistics/1280625/number-of-living-languages-in-africa-by-country/
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    Dataset updated
    Jun 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Africa
    Description

    As of 2022, there were over 2,000 living languages in Africa. With 520 languages, Nigeria accounted for around a fourth of the total languages spoken in Africa. Cameroon and the Democratic Republic of the Congo followed, each with over 200 living languages.

    Africa's linguistic diversity

    Africa boasted a repertoire of more than 2,000 living languages as of 2021. The continent had more than 900 classified as vigorous due to their widespread usage in face-to-face communication across all age groups. A regional perspective on the matter revealed that East Africa was Africa's most linguistically diverse region.

    Embracing diversity: Africans welcome ethnic diversity in neighbors

    In terms of cultural diversity, in 2021, the Republic of Chad held the title of being Africa's and the world's most culturally diverse nation. It obtained a cultural diversity index score of 0.85, with Cameroon and Nigeria following closely behind, scoring 0.84 and 0.83, respectively. The index measures diversity on a scale from zero to one, where one signifies the highest diversity level, while zero indicates the lowest level. Moreover, a survey conducted between 2019 and 2021 showed that Africans would be happy to have neighbors of different ethnicity.

  3. f

    Statistics of the Languages spoken in South Africa. For each language, we...

    • plos.figshare.com
    xls
    Updated Jun 5, 2025
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    Koena Ronny Mabokela; Mpho Primus; Turgay Celik (2025). Statistics of the Languages spoken in South Africa. For each language, we report the ISO, the African subfamily, and the prevalent countries where the language is also spoken. [Dataset]. http://doi.org/10.1371/journal.pone.0325102.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 5, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Koena Ronny Mabokela; Mpho Primus; Turgay Celik
    License

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

    Area covered
    Africa, South Africa
    Description

    Statistics of the Languages spoken in South Africa. For each language, we report the ISO, the African subfamily, and the prevalent countries where the language is also spoken.

  4. Number of living languages in Africa 2021, by region

    • statista.com
    Updated Jul 5, 2023
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    Statista (2023). Number of living languages in Africa 2021, by region [Dataset]. https://www.statista.com/statistics/1280562/number-of-living-languages-in-africa-by-region/
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    Dataset updated
    Jul 5, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    Africa
    Description

    As of 2021, there were over 2,000 living languages in Africa. The majority were in West Africa, counting 890 languages. The population of Central Africa spoke 678 different languages, while the number stood at 438 in East Africa. Southern Africa was the region with the lowest number of living languages in the continent.

  5. Total population of South Africa 2022, by ethnic groups

    • statista.com
    Updated Jun 3, 2025
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    Statista (2025). Total population of South Africa 2022, by ethnic groups [Dataset]. https://www.statista.com/statistics/1116076/total-population-of-south-africa-by-population-group/
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    Dataset updated
    Jun 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    South Africa
    Description

    As of 2022, South Africa's population increased and counted approximately 60.6 million inhabitants in total, of which the majority (roughly 49.1 million) were Black Africans. Individuals with an Indian or Asian background formed the smallest population group, counting approximately 1.56 million people overall. Looking at the population from a regional perspective, Gauteng (includes Johannesburg) is the smallest province of South Africa, though highly urbanized with a population of nearly 16 million people.

    Increase in number of households

    The total number of households increased annually between 2002 and 2022. Between this period, the number of households in South Africa grew by approximately 65 percent. Furthermore, households comprising two to three members were more common in urban areas (39.2 percent) than they were in rural areas (30.6 percent). Households with six or more people, on the other hand, amounted to 19.3 percent in rural areas, being roughly twice as common as those in urban areas.

    Main sources of income

    The majority of the households in South Africa had salaries or grants as a main source of income in 2019. Roughly 10.7 million drew their income from regular wages, whereas 7.9 million households received social grants paid by the government for citizens in need of state support.

  6. i

    Project for Statistics on Living Standards and Development 1993 - South...

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +2more
    Updated Mar 29, 2019
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    Southern Africa Labour and Development Research Unit (2019). Project for Statistics on Living Standards and Development 1993 - South Africa [Dataset]. https://datacatalog.ihsn.org/catalog/4628
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    Southern Africa Labour and Development Research Unit
    Time period covered
    1993
    Area covered
    South Africa
    Description

    Abstract

    The Project for Statistics on Living standards and Development was a coutrywide World Bank Living Standards Measurement Survey. It covered approximately 9000 households, drawn from a representative sample of South African households. The fieldwork was undertaken during the nine months leading up to the country's first democratic elections at the end of April 1994. The purpose of the survey was to collect statistical information about the conditions under which South Africans live in order to provide policymakers with the data necessary for planning strategies. This data would aid the implementation of goals such as those outlined in the Government of National Unity's Reconstruction and Development Programme.

    Geographic coverage

    National coverage

    Analysis unit

    • Households
    • Individuals
    • Community

    Universe

    All Household members.

    Individuals in hospitals, old age homes, hotels and hostels of educational institutions were not included in the sample. Migrant labour hostels were included. In addition to those that turned up in the selected ESDs, a sample of three hostels was chosen from a national list provided by the Human Sciences Research Council and within each of these hostels a representative sample was drawn on a similar basis as described above for the households in ESDs.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sample size is 9,000 households

    The sample design adopted for the study was a two-stage self-weightingdesign in which the first stage units were Census Enumerator Subdistricts (ESDs, or their equivalent) and the second stage were households.

    The advantage of using such a design is that it provides a representative sample that need not be based on accurate census population distribution.in the case of South Africa, the sample will automatically include many poor people, without the need to go beyond this and oversample the poor. Proportionate sampling as in such a self-weighting sample design offers the simplest possible data files for further analysis, as weights do not have to be added. However, in the end this advantage could not be retained and weights had to be added.

    The sampling frame was drawn up on the basis of small, clearly demarcated area units, each with a population estimate. The nature of the self-weighting procedure adopted ensured that this population estimate was not important for determining the final sample, however. For most of the country, census ESDs were used. Where some ESDs comprised relatively large populations as for instance in some black townships such as Soweto, aerial photographs were used to divide the areas into blocks of approximately equal population size. In other instances, particularly in some of the former homelands, the area units were not ESDs but villages or village groups.

    In the sample design chosen, the area stage units (generally ESDs) were selected with probability proportional to size, based on the census population. Systematic sampling was used throughout that is, sampling at fixed interval in a list of ESDs, starting at a randomly selected starting point. Given that sampling was self-weighting, the impact of stratification was expected to be modest. The main objective was to ensure that the racial and geographic breakdown approximated the national population distribution. This was done by listing the area stage units (ESDs) by statistical region and then within the statistical region by urban or rural. Within these sub-statistical regions, the ESDs were then listed in order of percentage African. The sampling interval for the selection of the ESDs was obtained by dividing the 1991 census population of 38,120,853 by the 300 clusters to be selected. This yielded 105,800. Starting at a randomly selected point, every 105,800th person down the cluster list was selected. This ensured both geographic and racial diversity (ESDs were ordered by statistical sub-region and proportion of the population African). In three or four instances, the ESD chosen was judged inaccessible and replaced with a similar one.

    In the second sampling stage the unit of analysis was the household. In each selected ESD a listing or enumeration of households was carried out by means of a field operation. From the households listed in an ESD a sample of households was selected by systematic sampling. Even though the ultimate enumeration unit was the household, in most cases "stands" were used as enumeration units. However, when a stand was chosen as the enumeration unit all households on that stand had to be interviewed.

    Census population data, however, was available only for 1991. An assumption on population growth was thus made to obtain an approximation of the population size for 1993, the year of the survey. The sampling interval at the level of the household was determined in the following way: Based on the decision to have a take of 125 individuals on average per cluster (i.e. assuming 5 members per household to give an average cluster size of 25 households), the interval of households to be selected was determined as the census population divided by 118.1, i.e. allowing for population growth since the census. It was subsequently discovered that population growth was slightly over-estimated but this had little effect on the findings of the survey.

    Individuals in hospitals, old age homes, hotels and hostels of educational institutions were not included in the sample. Migrant labour hostels were included. In addition to those that turned up in the selected ESDs, a sample of three hostels was chosen from a national list provided by the Human Sciences Research Council and within each of these hostels a representative sample was drawn on a similar basis as described abovefor the households in ESDs.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The main instrument used in the survey was a comprehensive household questionnaire. This questionnaire covered a wide range of topics but was not intended to provide exhaustive coverage of any single subject. In other words, it was an integrated questionnaire aimed at capturing different aspects of living standards. The topics covered included demography, household services, household expenditure, educational status and expenditure, remittances and marital maintenance, land access and use, employment and income, health status and expenditure and anthropometry (children under the age of six were weighed and their heights measured). This questionnaire was available to households in two languages, namely English and Afrikaans. In addition, interviewers had in their possession a translation in the dominant African language/s of the region.

    In addition to the detailed household questionnaire referred to above, a community questionnaire was administered in each cluster of the sample. The purpose of this questionnaire was to elicit information on the facilities available to the community in each cluster. Questions related primarily to the provision of education, health and recreational facilities. Furthermore there was a detailed section for the prices of a range of commodities from two retail sources in or near the cluster: a formal source such as a supermarket and a less formal one such as the "corner cafe" or a "spaza". The purpose of this latter section was to obtain a measure of regional price variation both by region and by retail source. These prices were obtained by the interviewer. For the questions relating to the provision of facilities, respondents were "prominent" members of the community such as school principals, priests and chiefs.

    Cleaning operations

    All the questionnaires were checked when received. Where information was incomplete or appeared contradictory, the questionnaire was sent back to the relevant survey organization. As soon as the data was available, it was captured using local development platform ADE. This was completed in February 1994. Following this, a series of exploratory programs were written to highlight inconsistencies and outlier. For example, all person level files were linked together to ensure that the same person code reported in different sections of the questionnaire corresponded to the same person. The error reports from these programs were compared to the questionnaires and the necessary alterations made. This was a lengthy process, as several files were checked more than once, and completed at the beginning of August 1994. In some cases questionnaires would contain missing values, or comments that the respondent did not know, or refused to answer a question.

    These responses are coded in the data files with the following values: VALUE MEANING -1 : The data was not available on the questionnaire or form -2 : The field is not applicable -3 : Respondent refused to answer -4 : Respondent did not know answer to question

    Data appraisal

    The data collected in clusters 217 and 218 should be viewed as highly unreliable and therefore removed from the data set. The data currently available on the web site has been revised to remove the data from these clusters. Researchers who have downloaded the data in the past should revise their data sets. For information on the data in those clusters, contact SALDRU http://www.saldru.uct.ac.za/.

  7. u

    Survey of Truth and Reconciliation in South Africa 2000-2001 - South Africa

    • datafirst.uct.ac.za
    Updated May 16, 2020
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    James L. Gibson (2020). Survey of Truth and Reconciliation in South Africa 2000-2001 - South Africa [Dataset]. http://www.datafirst.uct.ac.za/Dataportal/index.php/catalog/314
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    Dataset updated
    May 16, 2020
    Dataset authored and provided by
    James L. Gibson
    Time period covered
    2000 - 2001
    Area covered
    South Africa
    Description

    Abstract

    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 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 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 included those eliciting respondents views on the importance of revealing the truth about the past and achieving racial reconciliation.

    Geographic coverage

    The Survey of Truth and Reconciliation in South Africa, 2000-2001 had national coverage.

    Analysis unit

    Individuals

    Universe

    The universe under investigation included all South Africans aged 18+.

    Kind of data

    Sample survey data

    Sampling procedure

    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.

    The sampling was divided into two parts – a primary sample, including South Africans of all races, and a boost sample of white South Africans. In the main sample, 3,139 interviews were completed. The Boost Sample was composed only of white South Africans, with a control for language (English versus Afrikaans). A total of 588 additional whites was interviewed.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire for the Survey of Truth and Reconciliation in South Africa, 2000-2001 includes individual characteristics, respondent awareness, knowledge, and approval of the activities of the TRC, how important it was for respondents to find out the truth about the past and achieve racial reconciliation.

    Response rate

    The overall response rate for the survey was approximately 87 percent (after treating “break-offs” as unsuccessful interviews). The main reason for failing to complete the interview was inability to contact the respondent; refusal to be interviewed accounted for approximately 27 percent of the failed interviews. From the response rate alone, the representativeness of the sample seems assured. Such a high rate of response can be attributed to the general willingness of the South African population to be interviewed, the large number of call-backs we employed, and the use of an incentive for participating in the interview (the incentive was a magnetic torch (flashlight), with which the respondents were quite pleased).

  8. South African Census 1970 - South Africa

    • datafirst.uct.ac.za
    Updated Mar 28, 2020
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    Department of Statistics (now Statistics South Africa) (2020). South African Census 1970 - South Africa [Dataset]. http://www.datafirst.uct.ac.za/Dataportal/index.php/catalog/249
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    Dataset updated
    Mar 28, 2020
    Dataset provided by
    Statistics South Africahttp://www.statssa.gov.za/
    Authors
    Department of Statistics (now Statistics South Africa)
    Time period covered
    1970
    Area covered
    South Africa
    Description

    Abstract

    The 1970 South African Population Census collected data on dwellings and individuals' demographic, migration, family and employment details.

    Geographic coverage

    National coverage of 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, and the so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, Kwandebele, Transkei and Bophuthatswana.

    Analysis unit

    The units of analysis for the South African Census 1970 were households and individuals

    Universe

    The South African population census of 1970 covered all de jure household members (usual residents) of South Africa and the "national states".

    The 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 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]

    Sampling procedure

    The 1970 Census was a full count for Whites, Coloureds and Asians, and a 5% sample for Blacks (Africans)

    Sampling deviation

    The country was divided into 400 census districts for the 1970 Census. In most cases the boundaries of the census districts corresponded with those of the magisterial districts. However, in some cases the boundaries did not correspond, particularly in the areas in and around the "National States". This was to facilitate the administration of the census and to make it easier to exclude figures of the "National states" from provincial totals.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The 1970 Population Census of the Republic of South Africa questionnaires were: Form 01, to be completed by "Whites, Coloured and Asiatics" Form 02, to be completed by "Bantu" Form 03, for families, households and dwellings

    Form 01 collected data on relationship to household head, population group, sex, age, marital status, place of birth, and citizenship, as well as usual place of residence, home language, religion, level of education and income. Employment data collected included occupation, employment status and industry type.

    Form 02 collected data for African South Africans on relationship to household head, sex, age, marital status, fertility, place of birth, home language and literacy, religion and level of education. Employment data collected included occupation, employment status and industry type.

    Form 03 collected household data, including data on dwelling type, building material of dwelling walls, number of rooms and age of the dwelling. Data on home ownership. Data was also collected on the number and sex of household members and their relationship to the household head. Data on household heads included their population group, age and marital status. Income data was also collected, for husbands and wives. Data on home ownership, household size and domestic workers was also collected, but for Urban households only.

  9. Number of emigrants from South Africa 2020, by country of destination

    • statista.com
    Updated Jul 8, 2025
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    Statista (2025). Number of emigrants from South Africa 2020, by country of destination [Dataset]. https://www.statista.com/statistics/1238117/stock-of-emigrants-from-south-africa-by-country-of-destination/
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    Dataset updated
    Jul 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    South Africa
    Description

    In 2020, cumulative South African emigrants amounted to roughly *******. The vast majority settled in the United Kingdom (around *******), followed by Australia (nearly *******). Together, the two countries constituted roughly ** percent of the total South African migrants living abroad. Moreover, the third major country of destination for South Africans was the United States, with about ******* people living there. Overall, the ** countries presented covered **** percent of all South African migrants.

    Language: a primary driver of emigration destinations

    Language is a factor that helps ease communication and integration for individuals within a new society. Noticeably, the five leading destinations for South African emigrants had English as an official language. In South Africa, English was the second most spoken language outside households. Furthermore, the Netherlands ranked seventh, which language can also justify. Afrikaans, a language developed from ****-century Dutch, was the third most spoken language among households in South Africa.

    Unemployment a major worry and prevalent among youth    

    A real worry for South Africans in 2022 was unemployment. As of April 2022, ** percent of the respondents of a survey reported concern regarding the job market and the unemployment situation in the country. As of the first quarter of 2022, the unemployment rate among the age groups 15-24 years and 25-34 years was significantly higher than the rest, reaching **** percent and **** percent, respectively.

  10. Main languages spoken at home in Nigeria 2022

    • statista.com
    Updated Dec 15, 2023
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    Statista (2023). Main languages spoken at home in Nigeria 2022 [Dataset]. https://www.statista.com/statistics/1268798/main-languages-spoken-at-home-in-nigeria/
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    Dataset updated
    Dec 15, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 5, 2022 - Mar 31, 2022
    Area covered
    Nigeria
    Description

    The primary languages spoken at home in Nigeria are Hausa, Yoruba, and English. In a survey conducted in 2022 around 32 percent of respondents declared that they mainly spoke Hausa at home. Some 17 percent, on the other hand, had Yoruba as their main family language. Igbo followed, with 13 percent of the respondents indicating it. Some other languages spoken in Nigerian households are English, Ibibio, Fulani, Tiv, Nupe, Pidgin English, and Ijaw.

    One of the most diverse countries

    There are over 500 languages in Nigeria. The country has only one official language, English. According to estimates from 2018, Nigeria's major ethnic groups are Hausa, Yoruba, Igbo (Ibo), Fulani, Tiv, Kanuri, and Beriberi. Hausa, the largest population, is an ethnic group of people speaking the Hausa language. The Hausa are mainly present in West Africa, most of them living between Nigeria and Niger.

    English is the main language at school

    The main language of instruction at school is generally English. However, for the first years of education, an indigenous or local language is also taught. As of 2019, around 72 percent of young women and 78 percent of young men in Nigeria were English language literates. This means they could understand, read, and write a short and simple statement in English, for instance, on their everyday life.

  11. Census 2011 - South Africa

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Sep 18, 2014
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    Statistics South Africa (2014). Census 2011 - South Africa [Dataset]. https://microdata.worldbank.org/index.php/catalog/2067
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    Dataset updated
    Sep 18, 2014
    Dataset authored and provided by
    Statistics South Africahttp://www.statssa.gov.za/
    Time period covered
    2011
    Area covered
    South Africa
    Description

    Abstract

    Censuses are principal means of collecting basic population and housing statistics required for social and economic development, policy interventions, their implementation and evaluation.The census plays an essential role in public administration. The results are used to ensure: • equity in distribution of government services • distributing and allocating government funds among various regions and districts for education and health services • delineating electoral districts at national and local levels, and • measuring the impact of industrial development, to name a few The census also provides the benchmark for all surveys conducted by the national statistical office. Without the sampling frame derived from the census, the national statistical system would face difficulties in providing reliable official statistics for use by government and the public. Census also provides information on small areas and population groups with minimum sampling errors. This is important, for example, in planning the location of a school or clinic. Census information is also invaluable for use in the private sector for activities such as business planning and market analyses. The information is used as a benchmark in research and analysis.

    Census 2011 was the third democratic census to be conducted in South Africa. Census 2011 specific objectives included: - To provide statistics on population, demographic, social, economic and housing characteristics; - To provide a base for the selection of a new sampling frame; - To provide data at lowest geographical level; and - To provide a primary base for the mid-year projections.

    Geographic coverage

    National

    Analysis unit

    Households, Individuals

    Kind of data

    Census/enumeration data [cen]

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    About the Questionnaire : Much emphasis has been placed on the need for a population census to help government direct its development programmes, but less has been written about how the census questionnaire is compiled. The main focus of a population and housing census is to take stock and produce a total count of the population without omission or duplication. Another major focus is to be able to provide accurate demographic and socio-economic characteristics pertaining to each individual enumerated. Apart from individuals, the focus is on collecting accurate data on housing characteristics and services.A population and housing census provides data needed to facilitate informed decision-making as far as policy formulation and implementation are concerned, as well as to monitor and evaluate their programmes at the smallest area level possible. It is therefore important that Statistics South Africa collects statistical data that comply with the United Nations recommendations and other relevant stakeholder needs.

    The United Nations underscores the following factors in determining the selection of topics to be investigated in population censuses: a) The needs of a broad range of data users in the country; b) Achievement of the maximum degree of international comparability, both within regions and on a worldwide basis; c) The probable willingness and ability of the public to give adequate information on the topics; and d) The total national resources available for conducting a census.

    In addition, the UN stipulates that census-takers should avoid collecting information that is no longer required simply because it was traditionally collected in the past, but rather focus on key demographic, social and socio-economic variables.It becomes necessary, therefore, in consultation with a broad range of users of census data, to review periodically the topics traditionally investigated and to re-evaluate the need for the series to which they contribute, particularly in the light of new data needs and alternative data sources that may have become available for investigating topics formerly covered in the population census. It was against this background that Statistics South Africa conducted user consultations in 2008 after the release of some of the Community Survey products. However, some groundwork in relation to core questions recommended by all countries in Africa has been done. In line with users' meetings, the crucial demands of the Millennium Development Goals (MDGs) should also be met. It is also imperative that Stats SA meet the demands of the users that require small area data.

    Accuracy of data depends on a well-designed questionnaire that is short and to the point. The interview to complete the questionnaire should not take longer than 18 minutes per household. Accuracy also depends on the diligence of the enumerator and honesty of the respondent.On the other hand, disadvantaged populations, owing to their small numbers, are best covered in the census and not in household sample surveys.Variables such as employment/unemployment, religion, income, and language are more accurately covered in household surveys than in censuses.Users'/stakeholders' input in terms of providing information in the planning phase of the census is crucial in making it a success. However, the information provided should be within the scope of the census.

    1. The Household Questionnaire is divided into the following sections:
    2. Household identification particulars
    3. Individual particulars Section A: Demographics Section B: Migration Section C: General Health and Functioning Section D: Parental Survival and Income Section E: Education Section F: Employment Section G: Fertility (Women 12-50 Years Listed) Section H: Housing, Household Goods and Services and Agricultural Activities Section I: Mortality in the Last 12 Months The Household Questionnaire is available in Afrikaans; English; isiZulu; IsiNdebele; Sepedi; SeSotho; SiSwati;Tshivenda;Xitsonga

    4. The Transient and Tourist Hotel Questionnaire (English) is divided into the following sections:

    5. Name, Age, Gender, Date of Birth, Marital Status, Population Group, Country of birth, Citizenship, Province.

    6. The Questionnaire for Institutions (English) is divided into the following sections:

    7. Particulars of the institution

    8. Availability of piped water for the institution

    9. Main source of water for domestic use

    10. Main type of toilet facility

    11. Type of energy/fuel used for cooking, heating and lighting at the institution

    12. Disposal of refuse or rubbish

    13. Asset ownership (TV, Radio, Landline telephone, Refrigerator, Internet facilities)

    14. List of persons in the institution on census night (name, date of birth, sex, population group, marital status, barcode number)

    15. The Post Enumeration Survey Questionnaire (English)

    These questionnaires are provided as external resources.

    Cleaning operations

    Data editing and validation system The execution of each phase of Census operations introduces some form of errors in Census data. Despite quality assurance methodologies embedded in all the phases; data collection, data capturing (both manual and automated), coding, and editing, a number of errors creep in and distort the collected information. To promote consistency and improve on data quality, editing is a paramount phase in identifying and minimising errors such as invalid values, inconsistent entries or unknown/missing values. The editing process for Census 2011 was based on defined rules (specifications).

    The editing of Census 2011 data involved a number of sequential processes: selection of members of the editing team, review of Census 2001 and 2007 Community Survey editing specifications, development of editing specifications for the Census 2011 pre-tests (2009 pilot and 2010 Dress Rehearsal), development of firewall editing specifications and finalisation of specifications for the main Census.

    Editing team The Census 2011 editing team was drawn from various divisions of the organisation based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors. Census 2011 editing team was drawn from various divisions of the organization based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors.

    The Census 2011 questionnaire was very complex, characterised by many sections, interlinked questions and skipping instructions. Editing of such complex, interlinked data items required application of a combination of editing techniques. Errors relating to structure were resolved using structural query language (SQL) in Oracle dataset. CSPro software was used to resolve content related errors. The strategy used for Census 2011 data editing was implementation of automated error detection and correction with minimal changes. Combinations of logical and dynamic imputation/editing were used. Logical imputations were preferred, and in many cases substantial effort was undertaken to deduce a consistent value based on the rest of the household’s information. To profile the extent of changes in the dataset and assess the effects of imputation, a set of imputation flags are included in the edited dataset. Imputation flags values include the following: 0 no imputation was performed; raw data were preserved 1 Logical editing was performed, raw data were blank 2 logical editing was performed, raw data were not blank 3 hot-deck imputation was performed, raw data were blank 4 hot-deck imputation was performed, raw data were not blank

    Data appraisal

    Independent monitoring and evaluation of Census field activities Independent monitoring of the Census 2011 field activities was carried out by a team of 31 professionals and 381 Monitoring

  12. Number of native Spanish speakers worldwide 2024, by country

    • statista.com
    Updated Jan 15, 2025
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    Statista (2025). Number of native Spanish speakers worldwide 2024, by country [Dataset]. https://www.statista.com/statistics/991020/number-native-spanish-speakers-country-worldwide/
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    Dataset updated
    Jan 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    Mexico is the country with the largest number of native Spanish speakers in the world. As of 2024, 132.5 million people in Mexico spoke Spanish with a native command of the language. Colombia was the nation with the second-highest number of native Spanish speakers, at around 52.7 million. Spain came in third, with 48 million, and Argentina fourth, with 46 million. Spanish, a world language As of 2023, Spanish ranked as the fourth most spoken language in the world, only behind English, Chinese, and Hindi, with over half a billion speakers. Spanish is the official language of over 20 countries, the majority on the American continent, nonetheless, it's also one of the official languages of Equatorial Guinea in Africa. Other countries have a strong influence, like the United States, Morocco, or Brazil, countries included in the list of non-Hispanic countries with the highest number of Spanish speakers. The second most spoken language in the U.S. In the most recent data, Spanish ranked as the language, other than English, with the highest number of speakers, with 12 times more speakers as the second place. Which comes to no surprise following the long history of migrations from Latin American countries to the Northern country. Moreover, only during the fiscal year 2022. 5 out of the top 10 countries of origin of naturalized people in the U.S. came from Spanish-speaking countries.

  13. Number of households in South Africa 2002-2022

    • statista.com
    Updated Jun 3, 2025
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    Statista (2025). Number of households in South Africa 2002-2022 [Dataset]. https://www.statista.com/statistics/1112732/number-of-households-of-south-africa/
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    Dataset updated
    Jun 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    South Africa
    Description

    As of 2022, the number of households in South Africa increased and amounted to approximately 18.48 million, roughly 530,000 more than in the previous year. Between 2002 and 2022, the number of families in South Africa grew by around 65 percent. Looking at the number of households from a regional perspective , the Gauteng province (includes the city of Johannesburg) has the bulk of households, with almost 5.6 million residences. Although Gauteng is the smallest region in the country, it is highly urbanized and houses most of the population.

    Households headed by women

    The number of households headed by women averaged around 42 percent. Rural areas such as the Eastern Cape and Limpopo had a higher proportion of women in charge of their family unit. Urbanized regions, namely Gauteng and the Western Cape, were more likely to be headed by men.

    Languages spoken in households

    The most spoken language within and outside of South African households was isiZulu, with around 25 percent of the population utilizing it. The English language was the second most common language spoken outside of households, with a share of roughly 17 percent. However, within households, individuals preferred to speak other official languages such as isiXhosa and Afrikaans. South Africa has a diverse range of cultures, and language plays a crucial role in preserving these cultures.

  14. Reading literacy assessment of learners in South Africa 2021, by language

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Reading literacy assessment of learners in South Africa 2021, by language [Dataset]. https://www.statista.com/statistics/1394157/reading-literacy-assessment-of-learners-in-south-africa-by-language/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    South Africa
    Description

    The progress in international reading literacy study surveyed learners in grades four and six in ** official languages in South Africa. The highest language test score occurred among the grade six Afrikaans learners, with a mean score of ***. The grade four Afrikaans learners followed with a language test score of ***. On the other hand, Setswana had the lowest language test score with an average of ***, which is concerningly low when compared to the international average score of 500.

  15. Population Census 1970 - South Africa

    • dev.ihsn.org
    • datacatalog.ihsn.org
    • +2more
    Updated Apr 25, 2019
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    Statistics South Africa (2019). Population Census 1970 - South Africa [Dataset]. https://dev.ihsn.org/nada//catalog/73706
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    Dataset updated
    Apr 25, 2019
    Dataset authored and provided by
    Statistics South Africahttp://www.statssa.gov.za/
    Time period covered
    1970
    Area covered
    South Africa
    Description

    Abstract

    The 1970 South African Population Census was an enumeration of the population and housing in South Africa.The census collected data on dwellings and individuals' demographic, migration, family and employment details.

    Geographic coverage

    National coverage of 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, and the so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, Kwandebele, Transkei and Bophuthatswana.

    Analysis unit

    The units of analysis for the South African Census 1970 were households and individuals

    Universe

    The South African population census of 1970 covered all de jure household members (usual residents) of South Africa and the "national states".

    The 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 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]

    Sampling procedure

    The 1970 Census was a full count for Whites, Coloureds and Asians, and a 5% sample for Blacks (Africans)

    Sampling deviation

    The country was divided into 400 census districts for the 1970 Census. In most cases the boundaries of the census districts corresponded with those of the magisterial districts. However, in some cases the boundaries did not correspond, particularly in the areas in and around the "National States". This was to facilitate the administration of the census and to make it easier to exclude figures of the "National states" from provincial totals.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The 1970 Population Census of the Republic of South Africa questionnaires were: Form 01, to be completed by "Whites, Coloured and Asiatics" Form 02, to be completed by "Bantu" Form 03, for families, households and dwellings

    Form 01 collected data on relationship to household head, population group, sex, age, marital status, place of birth, and citizenship, as well as usual place of residence, home language, religion, level of education and income. Employment data collected included occupation, employment status and industry type.

    Form 02 collected data for African South Africans on relationship to household head, sex, age, marital status, fertility, place of birth, home language and literacy, religion and level of education. Employment data collected included occupation, employment status and industry type.

    Form 03 collected household data, including data on dwelling type, building material of dwelling walls, number of rooms and age of the dwelling. Data on home ownership. Data was also collected on the number and sex of household members and their relationship to the household head. Data on household heads included their population group, age and marital status. Income data was also collected, for husbands and wives. Data on home ownership, household size and domestic workers was also collected, but for Urban households only.

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Statista (2025). Distribution of languages spoken inside and outside of households South Africa 2018 [Dataset]. https://www.statista.com/statistics/1114302/distribution-of-languages-spoken-inside-and-outside-of-households-in-south-africa/
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Distribution of languages spoken inside and outside of households South Africa 2018

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27 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 3, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2018
Area covered
South Africa
Description

As of 2018, the languages most commonly spoken by individuals inside of South African households were isiZulu at 25.3 percent, isiXhosa at 14.8 percent and Afrikaans at 12.2 percent respectively. While English only accounts for the sixth most common language spoken inside of South African households at 8.1 percent, it is the second-most prevalent language spoken outside of homes, at 16.6 percent.

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