This dataset shows different breakdowns of London's resident population by their nationality. Data used comes from ONS' Annual Population Survey (APS).

The APS has a sample of around 320,000 people in the UK (around 28,000 in London). As such all figures must be treated with some caution. 95% confidence interval levels are provided.

Numbers have been rounded to the nearest thousand and figures for smaller populations have been suppressed.

Two files are available to download:

• Nationality - Borough: Shows nationality estimates in their broad groups such as European Union, South East Asia, North Africa, etc. broken down to borough level.
• Detailed Nationality - London: Shows nationality estimates for specific countries such as France, Bangladesh, Nigeria, etc. available for London as a whole.

A Tableau visualisation tool is also available.

Country of Birth data can be found here: https://data.london.gov.uk/dataset/country-of-birth

Nationality refers to that stated by the respondent during the interview. Country of birth is the country in which they were born. It is possible that an individual’s nationality may change, but the respondent’s country of birth cannot change. This means that country of birth gives a more robust estimate of change over time.

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.

This dataset shows different breakdowns of London's resident population by their country of birth. Data used comes from ONS' Annual Population Survey (APS).

The APS has a sample of around 320,000 people in the UK (around 28,000 in London). As such all figures must be treated with some caution. 95% confidence interval levels are provided.

Numbers have been rounded to the nearest thousand and figures for smaller populations have been suppressed.

Four files are available for download:

• Country of Birth - Borough: Shows country of birth estimates in their broad groups such as European Union, South East Asia, North Africa, etc. broken down to borough level.
• Detailed Country of Birth - London: Shows country of birth estimates for specific countries such as France, Bangladesh, Nigeria, etc. available for London as a whole
• Demography Update 09-2015: A GLA Demography report that uses APS data to analyse the trends in London for the period 2004 to 2014. A supporting data file is also provided.
• Country of Birth Borough 2004-2016 Analysis Tool: A tool produced by GLA Demography that allows users to explore different breakdowns of country of birth data.

An accompanying Tableau visualisation tool has also been produced which maps data from 2004 to 2015.

Nationality data can be found here: https://data.london.gov.uk/dataset/nationality

Nationality refers to that stated by the respondent during the interview. Country of birth is the country in which they were born. It is possible that an individual’s nationality may change, but the respondent’s country of birth cannot change. This means that country of birth gives a more robust estimate of change over time.

Abstract

In 1990 the Central Statistical Service of South Africa sponsored a household expenditure survey in a sub-set of households in 12 major metro/urban areas in the country. The aim of the survey was to obtain data on income and expenditure patterns of South African households on which the Consumer Price Index (CPS) and various other economic indicators could be based. The survey was conducted by Markdata, the fieldwork arm of the Human Sciences Research Council (HSRC). All population groups were enumerated but this dataset does not contain data files for the "white" population group.

Geographic coverage

The IES 1990 only collected data on expenditure from the 12 largest urban areas in the country, leaving out buying patters in small towns and rural areas. Areas enumerated were: Cape Peninsula, Port Elizabeth- Uitenhage, East London, Kimberley, Pietermaritz burg, Durban, Pretoria, Johannesburg, Witwatersrand (excl Jhb), Klerksdorp, Vaal Triangle, Orange Free State-Gold Fields, Bloemfontein.

Analysis unit

Units of analysis in the survey includes households and individuals

Universe

The survey covered all household members in the selected areas

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

Two survey instruments were provided in the IES 1990: A detailed "long" questionnaire and a "short" questionnaire without detailed classification of expenditure items. The "short" questionnaire was completed by two out of three households enumerated. The "short" and "long" questionnaires are identified separately in the variable q_type. "Long" questionnaires are indicated as questionnaire = 1 and "short' questionnaires as questionnaire = 2.