This statistic shows the share of the population in France in 2023, by nationality status. It appears that French-born citizens accounted for around 87 percent of the French population, while 8.2 percent of the people living in France in 2023 were foreigners.

This data collection consists of 161 selected social, demographic, and educational datasets for France in the period 1801-1897. The data were collected from published reports of three national statistical series: (1) National Censuses, (2) Vital Statistics, and (3) Primary Education. This project was supported by grants from the National Endowment for the Humanities and the National Science Foundation. The National Census data were derived from the quinquennial population censuses of France from 1801 to 1896 and were obtained from the Statistique Generale de la France. The data provide detailed social and economic information for the period 1851 to 1896. The data for 1801-1851 are less rich in subject matter coverage but do present some basic information on population characteristics. The National Census data in general describe the population, including the composition of the population by categories of age, sex, place of birth, marital status, religion, place of residence, and occupation. There is also some limited information on migration, transportation and communication, housing, and families. A large segment of the census data pertains to occupations of the population, specifying job classifications within professions, as well as information on non-employed household members that were dependent on employees in the various industries, in addition to enumerations of persons employed in various professions and trades. The Vital Statistics data files contain annual vital statistics for the French population. These data were obtained from two printed series, MOUVEMENT DE LA POPULATION (1801-1868), and STATISTIQUE ANNUELLE (1869-1897). The basic variables included in the vital statistics datasets record births, deaths, and marriages in France. Detailed cross-tabulations of these demographic indicators are presented for births, tabulated by sex, month, legitimacy status, and characteristics of the parents, and deaths, categorized by age and previous marital status of the partners. Additional cross-tabulations are provided for variables such as divorces, passports issued, medical personnel and hospitals, and a literacy indicator (signing of marriage certificates). The Primary Education data files provide information on primary schools and were obtained from the Statistique de l'enseignement Primaire. The data obtained from the series basically cover the period 1829-1897, although some recapitulative information for earlier years is also presented. The main focus of the data in this series is on primary schools, classes and buildings, enrollment, teachers, sources of funding and expenditure, and academic proficiency of the pupils. Additional information is included on literacy, teacher training (normal) schools, school age population, and libraries. A machine-readable French language codebook, describing the data items as well as the sources from which they were obtained, is provided with each dataset supplied. In addition, lists of the variables included in each dataset are included in Parts 162-164. See the related collection, DEMOGRAPHIC, SOCIAL, EDUCATIONAL AND ECONOMIC DATA FOR FRANCE, 1833-1925 (ICPSR 7529).

About this dataset

Context

The dataset tabulates the population of French Settlement by race. It includes the population of French Settlement across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of French Settlement across relevant racial categories.

Key observations

The percent distribution of French Settlement population by race (across all racial categories recognized by the U.S. Census Bureau): 94.80% are white, 0.92% are Black or African American and 4.28% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the French Settlement
• Population: The population of the racial category (excluding ethnicity) in the French Settlement is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of French Settlement total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for French Settlement Population by Race & Ethnicity. You can refer the same here

This statistic shows the total number of male births in France from 2004 to 2022. In 2004, there were 393,477 boys born in France. The number of male births in France peaked in 2010, with more than 410,000 births recorded. The number of boy births has been declining for many years; in 2022, the number dropped below 352,000.

This statistic shows the population distribution in France on January 1st, 2025, by age group. In 2025, people aged under 15 accounted for 16.7 percent of the total French population, whereas around 10 percent of the population were 75 years and older. By comparison, the number of members of the population over the age of 65 years has increased even more prominently, reaching 14.57 million in 2025. The number of people living in France has been steadily increasing since 1982, exceeding 68 million in 2025, having thus grown by seven percent during that time.

This statistic shows the distribution of the French population by origin as of January 1, 2021. It displays that 87.7 percent of the resident population acquired French nationality at birth.

France FR: Birth Rate: Crude: per 1000 People data was reported at 11.700 Ratio in 2016. This records a decrease from the previous number of 12.000 Ratio for 2015. France FR: Birth Rate: Crude: per 1000 People data is updated yearly, averaging 13.800 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 18.700 Ratio in 1961 and a record low of 11.700 Ratio in 2016. France FR: Birth Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank.WDI: Population and Urbanization Statistics. Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

About this dataset

Context

The dataset presents the median household income across different racial categories in French Lick. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of French Lick population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 80.91% of the total residents in French Lick. Notably, the median household income for White households is $49,722. Interestingly, despite the White population being the most populous, it is worth noting that Black or African American households actually reports the highest median household income, with a median income of $124,643. This reveals that, while Whites may be the most numerous in French Lick, Black or African American households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/french-lick-in-median-household-income-by-race.jpeg" alt="French Lick median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in French Lick.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for French Lick median household income by race. You can refer the same here

Prepared by ICPSR under a project to automate major portions of the Statistique Generale de la France, this is a collection of demographic, social, education, economic, population, and vital statistics data for France, 1833-1925. This conversion project is a continuation of one conducted in 1972, for which a similar data collection was created, SOCIAL, DEMOGRAPHIC, AND EDUCATIONAL DATA FOR FRANCE, 1801-1897 (ICPSR 0048). The project to collect and prepare these data was sponsored by two French and two American groups: ICPSR and the Center for Western European Studies at the University of Michigan, and the Fourth and Sixth Sections of the Ecole Pratique des Hautes Etudes and Conseil National de la Recherches Scientifique in France. Both collections include data recorded at the departement, arrondissement, chef-lieu, and ville level. In this collection, materials from the vital statistics series were prepared for selected years rather than for each year in the period from 1900-1925. The years that were chosen clustered around the quinquennial censuses and also included (because of the violent demographic dislocations produced by World War I) each year in the 1914-1919 period. In addition, some vital statistics for the nineteenth century (1836-1850, 1880, and 1892) obtained from fugitive published volumes that could not be located during the course of the 1972 project were prepared. The 136 datasets in this collection contain: (1) French population, economic, and social data obtained from the quenquennial censuses of 1901, 1906, 1911, and 1921, that detail the composition of the population by categories of age, sex, nativity, marital status, religion, place of residence, and occupation, (2) industrial census data for the years 1861-1896, (3) data on primary education in France for 1833, 1901, and 1906, as well as data on secondary and higher education in France for the years 1836-1850, 1880, and 1892, and (4) data from a separate series of annual vital statistics (Mouvement de la Population) that cover the years 1836-1850, 1892, and 1900-1925, citing births, deaths, and marriages in the nation.

France: Demographic pressures, 0 (low) - 10 (high): The latest value from 2024 is 2.8 index points, a decline from 3.1 index points in 2023. In comparison, the world average is 5.80 index points, based on data from 176 countries. Historically, the average for France from 2007 to 2024 is 3.12 index points. The minimum value, 1.9 index points, was reached in 2020 while the maximum of 4.1 index points was recorded in 2007.

According to a ********** survey, the share of young French respondents without access to a banking account virtually disappeared between 2017 and 2024. The decline in this particular group of respondents stood out compared to other demographics, and is likely the main cause of why the "unbanked" population - or those who or those who did not access to the services of a bank or another, similar financial organization - declined from *** percent in 2017 to *** percent by 2021. The report adds that men in France were more likely than women to be financially excluded from services like ATM machines, credit cards, or financial products like insurance or mortgages. The declining figures for unbanked population are reflected in the decreasing market share of cash in French physical stores.

In 2025, the Ile-de-France region, sometimes called the Paris region, was the most populous in France. It is located in the northern part of France, divided into eight departments and crossed by the Seine River. The region contains Paris, its large suburbs, and several rural areas. The total population in metropolitan France was estimated at around ** million inhabitants. In the DOM (Overseas Department), France had more than *** million citizens spread over the islands of Guadeloupe, Martinique, Reunion, Mayotte, and the South American territory of French Guiana. Ile-de-France: the most populous region in France According to the source, more than ** million French citizens lived in the Ile-de-France region. Ile-de-France was followed by Auvergne-Rhône-Alpes and Occitanie region which is in the Southern part of the country. Ile-de-France is not only the most populated region in France, it is also the French region with the highest population density. In 2020, there were ******* residents per square kilometer in Ile-de-France compared to ***** for Auvergne-Rhône-Alpes, the second most populated region in France. More than two million people were living in the city of Paris in 2025. Thus, the metropolitan area outside the city of Paris, called the suburbs or banlieue in French, had more than ten million inhabitants. Ile-de-France concentrates the majority of the country’s economic and political activities. An urban population In 2024, the total population of France amounted to over 68 million. The population in the country has increased since the mid-2000s. As well as the other European countries, France is experiencing urbanization. In 2023, more than ** percent of the French population lived in cities. This phenomenon shapes France’s geography.

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

The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.

PARES Dataset v2 PARES (PArish REcord Survey) contains 535 images of handwritten census tables for years ranging from around 1650 A.D. until 1850 A.D..They come from two French cities, Vic-sur-Seille (French department of Moselle) and Echevronne (French department of Côte d'Or). While they mention very ancient times, the documents are handwritten transcriptions of even older documents and are quite recent, copied from original documents during the 1950's and 1960's for demographic studies led by the INED in France (Institut National des études démographiques − National Institute for Demographic Studies). These copies were made by only a few different writers. The documents are damaged and exhibit different types of degradations. We identified seven different document categories we call C1 to C7. C1 and C3 are generally high-quality documents, without serious damage, consisting of about 90% of the dataset. Other categories include highly damaged documents or documents with specificities. A notable aspect of this dataset is that the records are written using only two different physical paper templates. Categories n°1, 2, 3, 6 and 7 have 25 recordings while the categories 4 and 5 are higher and can record up to 35 recordings. C4 and C5 are the larger templates and differ from the rest of the documents. We published a paper, Text Line Detection in Historical Index Tables: Evaluations on a New French PArish REcord Survey Dataset (PARES), in which we better describe the dataset and the tasks it's possible to run on it.

This upload contains two Geopackage files of raw data used for urban analysis in the outskirts of Lille and Nice, France. 
The data include building footprints (layer "building"), roads (layer "road"), and administrative boundaries (layer "adm_boundaries")
extracted from version 3.3 of the French dataset BD TOPO®3 (IGN, 2023) for the municipalities of Santes, Hallennes-lez-Haubourdin,
Haubourdin, and Emmerin in northern France (Geopackage "DPC_59.gpkg") and Drap, Cantaron and La Trinité in southern France 
(Geopackage "DPC_06.gpkg").

Metadata for these layers is available here: https://geoservices.ign.fr/sites/default/files/2023-01/DC_BDTOPO_3-3.pdf

Additionally, this upload contains the results of the following algorithms available in GitHub (https://github.com/perezjoan/emc2-WP2?tab=readme-ov-file)

1. The identification of main streets using the QGIS plugin Morpheo (layers "road_morpheo" and "buffer_morpheo") 
https://plugins.qgis.org/plugins/morpheo/ 

2. The identification of main streets in local contexts – connectivity locally weighted (layer "road_LocRelCon")

3. Basic morphometry of buildings (layer "building_morpho")

4. Evaluation of the number of dwellings within inhabited buildings (layer "building_dwellings")

5. Projecting population potential accessible from main streets (layer "road_pop_results")

Project website: http://emc2-dut.org/

Publications using this sample data: 
Perez, J. and Fusco, G., 2024. Potential of the 15-Minute Peripheral City: Identifying Main Streets and Population Within Walking Distance. In: O. Gervasi, B. Murgante, C. Garau, D. Taniar, A.M.A.C. Rocha and M.N. Faginas Lago, eds. Computational Science and Its Applications – ICCSA 2024 Workshops. ICCSA 2024. Lecture Notes in Computer Science, vol 14817. Cham: Springer, pp.50-60. https://doi.org/10.1007/978-3-031-65238-7_4.

Acknowledgement. This work is part of the emc2 project, which received the grant ANR-23-DUTP-0003-01 from the French National Research Agency (ANR) within the DUT Partnership.

There were 47 300 000 Facebook users in France in May 2024, which accounted for 70.5% of its entire population. The majority of them were women - 52.9%. People aged 25 to 34 were the largest user group (11 800 000). The highest difference between men and women occurs within people aged 65 and above, where women lead by 2 000 000.

BackgroundTesting was the cornerstone of the COVID-19 epidemic response in most countries until vaccination became available for the general population. Social inequalities generally affect access to healthcare and health behaviors, and COVID-19 was rapidly shown to impact deprived population more drastically. In support of the regional health agency in Provence-Alpes-Côte d’Azur (PACA) in South-Eastern France, we analyzed the relationship between testing rate and socio-demographic characteristics of the population, to identify gaps in testing coverage and improve targeting of response strategies.MethodsWe conducted an ecological analysis of SARS-CoV-2/COVID-19 testing rate in the PACA region, based on data aggregated at the finest spatial resolution available in France (IRIS) and by periods defined by public health implemented measures and major epidemiological changes. Using general census data, population density, and specific deprivation indices, we used principal component analysis followed by hierarchical clustering to define profiles describing local socio-demographic characteristics. We analyzed the association between these profiles and testing rates in a generalized additive multilevel model, adjusting for access to healthcare, presence of a retirement home, and the age profile of the population.ResultsWe identified 6 socio-demographic profiles across the 2,306 analyzed IRIS spatial units: privileged, remote, intermediate, downtown, deprived, and very deprived (ordered by increasing social deprivation index). Profiles also ranged from rural (remote) to high density urban areas (downtown, very deprived). From July 2020 to December 2021, we analyzed SARS-CoV-2/COVID-19 testing rate over 10 periods. Testing rates fluctuated strongly but were highest in privileged and downtown areas, and lowest in very deprived ones. The lowest adjusted testing rate ratios (aTRR) between privileged (reference) and other profiles occurred after implementation of a mandatory healthpass for many leisure activities in July 2021. Periods of contextual testing near Christmas displayed the largest aTRR, especially during the last periods of 2021 after the end of free convenience testing for unvaccinated individuals.ConclusionWe characterized in-depth local heterogeneity and temporal trends in testing rates and identified areas and circumstances associated with low testing rates, which the regional health agency targeted specifically for the deployment of health mediation activities.

This graph shows the estimated population in the city of Paris from 1989 to 2025. It appears that the number of inhabitants in the French capital decreased since 2012 and from 2.24 million Parisians that year down to 2.05 million in 2025. The high price of rents in the French capital might explain why a lot of people leave Paris to live in cheaper cities in France or the Paris agglomeration.

The empirical dataset is derived from a survey carried out on 25 estates in 14 cities in nine different European countries: France (Lyon), Germany (Berlin), Hungary (Budapest and Nyiregyha´za), Italy (Milan), the Netherlands (Amsterdam and Utrecht), Poland (Warsaw), Slovenia (Ljubljana and Koper), Spain (Barcelona and Madrid), and Sweden (Jo¨nko¨ping and Stockholm). The survey was part of the EU RESTATE project (Musterd & Van Kempen, 2005). A similar survey was constructed for all 25 estates.

The survey was carried out between February and June 2004. In each case, a random sample was drawn, usually from the whole estate. For some estates, address lists were used as the basis for the sample; in other cases, the researchers first had to take a complete inventory of addresses themselves (for some deviations from this general trend and for an overview of response rates, see Musterd & Van Kempen, 2005). In most cities, survey teams were hired to carry out the survey. They worked under the supervision of the RESTATE partners. Briefings were organised to instruct the survey teams. In some cases (for example, in Amsterdam and Utrecht), interviewers were recruited from specific ethnic groups in order to increase the response rate among, for example, the Turkish and Moroccan residents on the estates. In other cases, family members translated questions during a face-to-face interview. The interviewers with an immigrant background were hired in those estates where this made sense. In some estates it was not necessary to do this because the number of immigrants was (close to) zero (as in most cases in CE Europe).

The questionnaire could be completed by the respondents themselves, but also by the interviewers in a face-to-face interview.

Data and Representativeness

The data file contains 4756 respondents. Nearly all respondents indicated their satisfaction with the dwelling and the estate. Originally, the data file also contained cases from the UK.

However, UK respondents were excluded from the analyses because of doubts about the reliability of the answers to the ethnic minority questions. This left 25 estates in nine countries. In general, older people and original populations are somewhat over-represented, while younger people and immigrant populations are relatively under-represented, despite the fact that in estates with a large minority population surveyors were also employed from minority ethnic groups. For younger people, this discrepancy probably derives from the extent of their activities outside the home, making them more difficult to reach. The under-representation of the immigrant population is presumably related to language and cultural differences. For more detailed information on the representation of population in each case, reference is made to the reports of the researchers in the different countries which can be downloaded from the programme website. All country reports indicate that despite these over- and under-representations, the survey results are valuable for the analyses of their own individual situation.

This dataset is the result of a team effort lead by Professor Ronald van Kempen, Utrecht University with funding from the EU Fifth Framework.