Comprehensive demographic dataset for Johannesburg, MI, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Historical dataset of population level and growth rate for the Johannesburg, South Africa metro area from 1950 to 2025.

As of 2023, South Africa's population increased and counted approximately 62.3 million inhabitants in total, of which the majority inhabited Gauteng, KwaZulu-Natal, and the Western-Eastern Cape. Gauteng (includes Johannesburg) is the smallest province in South Africa, though highly urbanized with a population of over 16 million people according to the estimates. Cape Town, on the other hand, is the largest city in South Africa with nearly 3.43 million inhabitants in the same year, whereas Durban counted 3.12 million citizens. However, looking at cities including municipalities, Johannesburg ranks first. High rate of young population South Africa has a substantial population of young people. In 2024, approximately 34.3 percent of the people were aged 19 years or younger. Those aged 60 or older, on the other hand, made-up over 10 percent of the total population. Distributing South African citizens by marital status, approximately half of the males and females were classified as single in 2021. Furthermore, 29.1 percent of the men were registered as married, whereas nearly 27 percent of the women walked down the aisle. Youth unemployment Youth unemployment fluctuated heavily between 2003 and 2022. In 2003, the unemployment rate stood at 36 percent, followed by a significant increase to 45.5 percent in 2010. However, it fluctuated again and as of 2022, over 51 percent of the youth were registered as unemployed. Furthermore, based on a survey conducted on the worries of South Africans, some 64 percent reported being worried about employment and the job market situation.

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.

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.

South Africa is the sixth African country with the largest population, counting approximately 60.5 million individuals as of 2021. In 2023, the largest city in South Africa was Cape Town. The capital of Western Cape counted 3.4 million inhabitants, whereas South Africa's second largest city was Durban (eThekwini Municipality), with 3.1 million inhabitants. Note that when observing the number of inhabitants by municipality, Johannesburg is counted as largest city/municipality of South Africa.

From four provinces to nine provinces

Before Nelson Mandela became president in 1994, the country had four provinces, Cape of Good Hope, Natal, Orange Free State, and Transvaal and 10 “homelands” (also called Bantustans). The four larger regions were for the white population while the homelands for its black population. This system was dismantled following the new constitution of South Africa in 1996 and reorganized into nine provinces. Currently, Gauteng is the most populated province with around 15.9 million people residing there, followed by KwaZulu-Natal with 11.68 million inhabiting the province. As of 2022, Black African individuals were almost 81 percent of the total population in the country, while colored citizens followed amounting to around 5.34 million.

A diverse population

Although the majority of South Africans are identified as Black, the country’s population is far from homogenous, with different ethnic groups usually residing in the different “homelands”. This can be recognizable through the various languages used to communicate between the household members and externally. IsiZulu was the most common language of the nation with around a quarter of the population using it in- and outside of households. IsiXhosa and Afrikaans ranked second and third with roughly 15 percent and 12 percent, respectively.

†Age at the time of the interview for the HCT cohort and the pre-ART cohort and at initiation for the ART cohort.‡Unmarried includes patients who reported being single, divorced/separated, and widowed.¥Employed includes patients who reported formal employment, informal employment, and self-employment. Unemployed includes those who reported no employment, studying, being retired, performing community service, and other. at the time of the interview for the HCT cohort, first CD4 count conducted for the pre-ART cohort and at baseline for the ART cohort.Demographic and Clinical Characteristics of Three Cohorts of Patients Enrolled in Different Stages of HIV care in Johannesburg, South Africa.

As of 2024, South Africa's population increased, counting approximately 63 million inhabitants. Of these, roughly 27.5 million were aged 0-24, while 654,000 people were 80 years or older. Gauteng and Cape Town are the most populated South Africa’s yearly population growth has been fluctuating since 2013, with the growth rate dropping below the world average in 2024. The majority of people lived in the borders of Gauteng, the smallest of the nine provinces in terms of land area. The number of people residing there amounted to 16.6 million in 2023. Although the Western Cape was the third-largest province, the city of Cape Town had the highest number of inhabitants in the country, at 3.4 million. An underemployed younger population South Africa has a large population under 14, who will be looking for job opportunities in the future. However, the country's labor market has had difficulty integrating these youngsters. Specifically, as of the fourth quarter of 2024, the unemployment rate reached close to 60 percent and 384 percent among people aged 15-24 and 25–34 years, respectively. In the same period, some 27 percent of the individuals between 15 and 24 years were economically active, while the labor force participation rate was higher among people aged 25 to 34, at 74.3 percent.

Part of the British Academy Knowledge Frontiers: International Interdisciplinary Research funding programme. Funded by the Department for Business, Energy and Industrial Strategy (BEIS). We are one of nine research projects bringing together novel, interdisciplinary ideas from across the humanities and social sciences in collaboration with the natural, medical and engineering sciences to propose solutions to international challenges past, present and future.• Theme of ‘What is a good city?’• 2-year projects with interdisciplinary and international teams• Projects “strengthen understanding of international challenges … and engage with questions concerning the relationship between expertise, public understanding and policy delivery internationally.” (British Academy)This research project investigated the challenge of food insecurity in cities as experienced by migrant communities and explored the role of traditional foods in well-being. The global population is increasingly urbanised, with Sub-Saharan Africa experiencing the fastest rate of urban population growth. South Africa is a centre for regional migration, with Johannesburg being the destination for the largest proportion of both within-country and international migrants. The project focused on two migrant groups in Johannesburg - South African rural-to-urban migrants and international regional migrants. Urban populations are dependent on food markets for daily sustenance and nutrition, hence access to affordable, acceptable and nutritious food through markets must be prioritised by cities. By identifying the drivers of food choice in urban migrant and immigrant populations around traditional foods, barriers to consumption and engaging with those involved in knowledge in urban planning and development, this project aimed to go some way towards tackling the problem of urban food insecurity and malnutrition.

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

Abstract

This dataset is from the Gauteng City-Region Observatory which is a partnership between the University of Johannesburg, the University of the Witwatersrand, the Gauteng Provincial Government and several Gauteng municipalities, including the Gauteng Provincial Government, as well as the South African Local Government Association (SALGA). The GCRO conducted Quality of Life Surveys in 2009 (Round 1), 2011 (Round 2), 2013-2014 (Round 3) and 2015-2016 (Round 4), 2017-2018 (Round 5), and 2020-2021 ( Round 6). Round 7 took place from 11 September 2023 to 19 April 2024 and is the latest round of the survey.

Geographic coverage

The survey covers the Gauteng Province in South Africa.

Analysis unit

Households and individuals

Universe

The survey covers all adult residents in Gauteng Province, South Africa.

Kind of data

Sample survey data

Mode of data collection

Face-to-face

Research instrument

GCRO conducted a consultative process for the questionnaire for the Quality of Life Survey Round 7 during which various modules were integrated into the Round 7 questionnaire. These modules include Administrative, Demographics, Core services, Environment/Sustainability, Governance, Health, Social mobility, Economic, Social cohesion, Community attitudes, Transport, Experiences of violence, Life satisfaction, Crime and Safety, and Migration.

This anonymized dataset contains demographic, epidemiological, treatment, and outcomes data of 224 patients diagnosed and treated for acute kidney injury at Helen Joseph Hospital between 1/7/2020 and 31/12/2021.

DWD’s fully automatic MOSMIX product optimizes and interprets the forecast calculations of the NWP models ICON (DWD) and IFS (ECMWF), combines these and calculates statistically optimized weather forecasts in terms of point forecasts (PFCs). Thus, statistically corrected, updated forecasts for the next ten days are calculated for about 5400 locations around the world. Most forecasting locations are spread over Germany and Europe. MOSMIX forecasts (PFCs) include nearly all common meteorological parameters measured by weather stations. For further information please refer to: [in German: https://www.dwd.de/DE/leistungen/met_verfahren_mosmix/met_verfahren_mosmix.html ] [in English: https://www.dwd.de/EN/ourservices/met_application_mosmix/met_application_mosmix.html ]

CN: Total Scheduled Flight: South Africa: Johannesburg-Beijing data was reported at 6.000 Unit in 24 Nov 2025. This stayed constant from the previous number of 6.000 Unit for 17 Nov 2025. CN: Total Scheduled Flight: South Africa: Johannesburg-Beijing data is updated weekly, averaging 6.000 Unit from Dec 2018 (Median) to 24 Nov 2025, with 206 observations. The data reached an all-time high of 9.000 Unit in 30 Dec 2019 and a record low of 2.000 Unit in 20 Mar 2023. CN: Total Scheduled Flight: South Africa: Johannesburg-Beijing data remains active status in CEIC and is reported by VariFlight. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TM: VariFlight Flight Statistics: Total Scheduled Flight: Arrival: Beijing.

Total Cancellation Rate: South Africa: Johannesburg-Sichuan: Chengdu data was reported at 100.000 % in 15 May 2023. This stayed constant from the previous number of 100.000 % for 10 Apr 2023. Total Cancellation Rate: South Africa: Johannesburg-Sichuan: Chengdu data is updated weekly, averaging 100.000 % from Dec 2022 (Median) to 15 May 2023, with 10 observations. The data reached an all-time high of 100.000 % in 15 May 2023 and a record low of 0.000 % in 09 Jan 2023. Total Cancellation Rate: South Africa: Johannesburg-Sichuan: Chengdu data remains active status in CEIC and is reported by VariFlight. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TM: VariFlight Flight Statistics: Total Cancellation Rate: Arrival: Sichuan.

This anonymized database contains the de-identified demographic data and reasons for exclusion from kidney transplantation of 400 patients undergoing transplant evaluation at the Helen Joseph Hospital during the period 1/1/2018 - 31/12/2023.

Financial overview and grant giving statistics of Johannesburg Jewish Helping Hand - US

Abstract

The South Africa Enterprise Survey was conducted between January and December 2007. Data from 1057 establishments in private manufacturing and services sectors were analyzed. The sample included enterprises with more than four employees (937 companies) as well as micro firms, establishments with less than 5 workers, (120 observations). The survey targeted establishments in Johannesburg, Cape Town, Port Elizabeth and Durban.

The objective of the survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The South Africa Enterprise Survey 2007 included enterprises with more than four employees as well as micro establishments, firms with less than five workers. There are 120 micro establishments in the sample.

The sample for enterprises with more than four employees was designed using stratified random sampling with strata defined by region, sector and firm size.

Establishments located in Johannesburg, Cape Town, Port Elizabeth and Durban were interviewed.

Following the ISIC (revision 3.1) classification, the following industries were targeted: all manufacturing sectors (group D), construction (group F), retail and wholesale services (subgroups 52 and 51 of group G), hotels and restaurants (group H), transport, storage, and communications (group I), and computer and related activities (sub-group 72 of group K). For establishments with five or more full-time permanent paid employees, this universe was stratified according to the following categories of industry: 1. Manufacturing: Food and Beverages (Group D, sub-group 15), Machinery and Equipment (Group D, sub-group 29), Electrical Machinery and Equipment (Group D, sub-group 31); 2. Manufacturing: Textiles (Group D, sub-group 17), Garment (Group D, sub-group 18), Leather and Footwear (Group D, sub-group 19), Paper and Paper Products (Group D, sub-group 21), Printing and Publishing (Group D, sub-group 22); 3. Manufacturing: Non-Metallic Mineral Products (Group D, sub-group 26), Basic Metals (Group D, sub-group 27), Fabricated Metal Products (Group D, sub-group 28); 4. Manufacturing: Wood and Wood Products (Group D, sub-group 20), Furniture (Group D, sub-group 36) 5. Manufacturing: Refined Petroleum Products (Group D, sub-group 23), Chemical Products (Group D, sub-group 24), Rubber and Plastics (Group D, sub-group 25) 6. Retail Trade: (Group G, sub-group 52); 7. Rest of the universe, including: • Other Manufacturing (Group D excluding sub-groups in strata 1-5); • Construction (Group F); • Wholesale trade (Group G, sub-group 51); • Hotels, bars and restaurants (Group H); • Transportation, storage and communications (Group I); • Computer related activities (Group K, sub-group 72).

Size stratification was defined following the standardized definition used for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers.

The implementing agency (EEC Canada) was unable to obtain a satisfactory sample frame from South African statistical agency (STASA) or its Department of Revenue. The best alternative solution was a list obtained from the Department of Trade and Industry Companies and Intellectual Property Registration Office (CIPRO), which contained about 800000 establishments when delineating in-scope cities and industries, but which had incomplete firm characteristics necessary for stratification purposes (e.g. contact information, size). In order to determine the sample frame, EEC Canada randomly drew 9550 units and contacted them.

In South Africa, the survey included panel data collected from establishments surveyed in the 2003 Investment Climate Survey (ICS) of South Africa. That survey included establishments in the manufacturing and the rest of universe strata, distributed across Gauteng (Johannesburg), KwaZulu Natal (Durban), Western Cape (Cape Town) and Eastern Cape (Port Elizabeth) provinces.

In order to collect the largest possible set of panel data, an attempt was made to contact and survey valid establishments (579) in the panel list provided which was part of the Enterprise Survey's scope. Of the 716 establishments provided to EEC Canada from those surveyed in 2003, there were 35 doubles, 8 out-of-scope, 89 excluded from this survey by The World Bank to avoid over representing Construction in a single Residual stratum, and 5 with undefined ISIC codes. This left a total potential of 579 panel establishments. EEC Canada surveyed 231 panel establishments or 40% of the total potential panels without eliminating those establishments which had closed. Once eliminated, this percentage coverage exceeded 55%. Given the non-random nature of panel establishment selection, these establishments are not allocated probability weights in the final dataset.

In this survey, the micro establishment stratum covers all establishments of the targeted categories of economic activity with less than 5 employees located in Johannesburg. The implementing agency selected an aerial sampling approach to estimate the population of establishments and select the sample in this stratum for all states of the survey.

First, to randomly select individual micro establishments for surveying, the following procedure was followed: i) select districts and specific zones of each district where there was a high concentration of micro establishments; ii) count all micro establishments in these specific zones; iii) based on this count, create a virtual list and select establishments at random from that virtual list; and iv) based on the ratio between the number selected in each specific zone and the total population in that zone, create and apply a skip rule for selecting establishments in that zone.

The districts and the specific zones were selected at first according to local sources. The EEC team then went in the field to verify the sources and to count micro establishments. Once the count for each zone was completed, the numbers were sent back to EEC head office in Montreal.

At the head office, the count by zone was converted into one list of sequential numbers for the whole survey region, and a computer program performed a random selection of the determined number of establishments from the list. Then, based on the number that the computer selected in each specific zone, a skip rule was defined to select micro establishments to survey in that zone. The skip rule for each zone was sent back to the EEC field team.

In Johannesburg, enumerators were sent to each zone with instructions how to apply the skip rule defined for that zone as well as how to select replacements in the event of a refusal or other cause of non-participation.

For complete information about sampling methodology, refusal rate and weighting please review "South Africa Enterprise Survey 2007 Implementation Report" in "Technical Documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Micro

The Egyptian capital, Cairo, is the largest agglomeration on the African continent. In 2023, almost ** million people resided in Greater Cairo (consisting of parts of three governorates). Johannesburg-Pretoria, South Africa, and Lagos, Nigeria, followed, with close to **** million and **** million inhabitants, respectively.

aAfrican donors belonged to any one of the 4 major ethnic groups living in South Africa. These include the Nguni, Sotho, Shangaan-Tsonga and Venda groups. The Nguni group can be subdivided into Zulu and Xhosa. Donors were collected in the Gauteng province of South Africa, residing in the urban region in and around Johannesburg.