This statistic shows the ten largest cities in France as of 2022. In 2022, around 2.11 million people lived in Paris, making it the largest city in France.

By 1800, London had grown to be the largest city in Western Europe with just under one million inhabitants. Paris was now the second largest city, with over half a million people, and Naples was the third largest city with 450 thousand people. The only other cities with over two hundred thousand inhabitants at this time were Vienna, Amsterdam and Dublin. Another noticeable development is the inclusion of many more northern cities from a wider variety of countries. The dominance of cities from France and Mediterranean countries was no longer the case, and the dispersal of European populations in 1800 was much closer to how it is today, more than two centuries later.

Actual value and historical data chart for France Population In The Largest City Percent Of Urban Population

This statistic shows the gross rental profitability of the 30 largest cities in France in 2019. At that time, Boulogne-Billancourt and Bordeaux were the French cities where the gross rental profitability was the lowest. In contrast, Limoges and Le Mans were the French cities with the highest gross rental profitability.

France FR: Population in Largest City data was reported at 10,844,847.000 Person in 2017. This records an increase from the previous number of 10,789,031.000 Person for 2016. France FR: Population in Largest City data is updated yearly, averaging 9,226,364.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 10,844,847.000 Person in 2017 and a record low of 7,410,735.000 Person in 1960. France FR: Population in Largest City 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: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

France FR: Population in Largest City: as % of Urban Population data was reported at 20.512 % in 2017. This records an increase from the previous number of 20.490 % for 2016. France FR: Population in Largest City: as % of Urban Population data is updated yearly, averaging 21.394 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 25.582 % in 1960 and a record low of 20.472 % in 2014. France FR: Population in Largest City: as % of Urban Population 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: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted Average;

This statistic shows the number of maternity hospitals in the ten largest cities in France in 2019. That year, there were ** maternity hospitals in Paris, compared to * in Marseille, the second largest city in France. The other top ten big cities in France have generally 2-3 maternity hospitals.

As of mid-2023, Paris recorded a public electric vehicle charging infrastructure index score of ** percent, indicative of how high the city's ratio of public chargers per 1,000 inhabitants was. The capital was the only French city to record an index score above ** percent. Strasbourg, which was second in the ranking, had a score of ** percent.

This statistic shows the number of dialysis centers in the ten largest cities of France in 2019. That year, there were 11 dialysis centers in Marseille, less than half the number of centers in Paris.

About this dataset

Context

This list ranks the 1 cities in the Major County, OK by French population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by French Population: This column displays the rank of city in the Major County, OK by their French population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• French Population: The French population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as French. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Major County French Population: This tells us how much of the entire Major County, OK French population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

It is estimated that the largest cities in Western Europe in 1330 were Paris and Granada. At this time, Paris was the seat of power in northern France, while Granada had become the largest multicultural city in southern Spain, controlled by the Muslim, Nasrid Kingdom during Spain's Reconquista period. The next three largest cities were Venice, Genoa and Milan, all in northern Italy, renowned as important trading cities during the middle ages. In October 1347, the first wave of the Black Death had arrived in Sicily and then began spreading throughout Europe, decimating the population.

About this dataset

Context

This list ranks the 964 cities in the Texas by French population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by French Population: This column displays the rank of city in the Texas by their French population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• French Population: The French population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as French. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Texas French Population: This tells us how much of the entire Texas French population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

The purported spatial segregation of Muslim populations in Western Europe constitutes a longstanding policy and scholarly concern, yet little spatial data exists for purposes of empirical study. The MAPISLAM dataset is a research effort aimed at bridging this gap for the French empirical context. MAPISLAM is a spatial dataset built from publicly available, online repositories of addresses for places of interest destined to the Muslim communities of France’s major cities.

This data set is composed by 5 geojson files, that can be used to generate maps of mainland France :

motifs_all.geojson : pattern about transport extracted from contributions of the French Great National Debate (Grand Débat National). Original dataset : https://granddebat.fr/pages/donnees-ouvertes

bikeway_fr.geojson and railroad_fr.geojson : cycleways and railways of mainland France, from Open Street Map. Original dataset : https://download.geofabrik.de/europe/france.html

trainstations.geojson : train stations and halts of mainland France, from Open Street Map. Original dataset : https://download.geofabrik.de/europe/france.html

au2010_carto.geojson : categorized urban areas of mainland France. Original dataset : https://www.insee.fr/fr/information/2115011

communesimportantes.geojson : the main cities of mainland France

The data set is in French.

Ce jeu de données est composé de 5 fichiers geojson qui peuvent être utilisés pour générer des cartes en France métropolitaine :

motifs_all.geojson : motifs à propos du transport extraient des contributions en ligne au Grand Débat National. Jeu de données d'origine : https://granddebat.fr/pages/donnees-ouvertes

bikeway_fr.geojson and railroad_fr.geojson : pistes cyclables et voies ferrées en France métropolitaine, venant d'Open Street Map. Jeu de données d'origine : https://download.geofabrik.de/europe/france.html

trainstations.geojson : gares et petites gares en France métropolitaine, from Open Street Map. Original dataset : https://download.geofabrik.de/europe/france.html

au2010_carto.geojson : aires urbaines catégorisées en France métropolitaine, définies par l'INSEE. Jeu de données d'origine : https://www.insee.fr/fr/information/2115011

communesimportantes.geojson : principales villes de France métropolitaine

About this dataset

Context

This list ranks the 2 cities in the Big Stone County, MN by French population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by French Population: This column displays the rank of city in the Big Stone County, MN by their French population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• French Population: The French population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as French. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Big Stone County French Population: This tells us how much of the entire Big Stone County, MN French population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

The catchment area of a city is a group of municipalities, of a single enclave and enclave, which defines the extent of the influence of a cluster of population and employment on the surrounding municipalities, this influence being measured by the intensity of commuting to work.

Urban area zoning follows the zoning into urban areas in 2010.

An area consists of a pole and a crown.

— Poles are determined mainly on the basis of density and total population criteria, using a methodology consistent with that of the municipal density grid. A threshold of jobs is added in order to prevent essentially residential municipalities with few jobs from being considered poles. Within the pole, the most populous commune is called the center commune. If a pole sends at least 15 % of its assets to work in another pole of the same level, the two poles are associated and together form the heart of a catchment area. — Municipalities that send at least 15 % of their assets to work in the pole are the crown of the area.

The definition of the largest catchment areas of cities is consistent with the definition of “cities” and “functional urban areas” used by Eurostat and the OECD to analyse the functioning of cities. Zoning into catchment areas thus facilitates international comparisons and makes it possible to visualise the influence in France of major foreign cities. For example, seven areas have a town located abroad (Bâle, Charleroi, Geneva, Lausanne, Luxembourg, Monaco and Saarbrücken).

The areas are classified according to the total number of inhabitants of the area in 2017. The main thresholds selected are: Paris, 700,000 inhabitants, 200,000 inhabitants and 50,000 inhabitants. Areas whose pole is located abroad are classified in the category corresponding to their total population (French and foreign).

Urban catchment areas, dated 2020, were constructed with reference to commuting known in the 2016 Census.

Downloadable files provide the characteristics of the city’s catchment areas (size slice, number of municipalities) and the municipal composition of the city’s catchment areas.

The France condominiums and apartments market is segmented by City (Paris, Lyon, Bordeaux, Marseille, and Other Cities). The report offers market sizes and forecasts in value (USD billion) for all the above segments.

The French residential real estate market, valued at €343.52 million in 2025, is projected to experience robust growth, driven by a compound annual growth rate (CAGR) of 6.75% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, a consistently strong demand for housing, particularly in urban centers like Paris and other major cities, coupled with limited supply, is pushing prices upward. Secondly, favorable government policies aimed at stimulating homeownership and supporting the construction industry contribute to market dynamism. The market is segmented primarily by property type, with apartments and condominiums comprising a significant share, followed by landed houses and villas. This segmentation reflects varying buyer preferences and affordability levels. Growth is further influenced by evolving consumer preferences, including increasing demand for sustainable and energy-efficient homes, leading developers to incorporate eco-friendly features into new constructions. While rising interest rates pose a potential restraint, the underlying demand and government support are expected to mitigate this impact, ensuring continued market expansion in the forecast period. Competitive forces within the sector, with prominent players like Sogeprom, Bouygues Immobilier, and Vinci Immobilier, drive innovation and efficiency within the industry. Regional variations are expected, with Paris and its surrounding Île-de-France region likely exhibiting stronger growth compared to other areas. The substantial growth forecast for the French residential market presents significant opportunities for investors and developers. However, managing risks associated with fluctuating interest rates and regulatory changes remains crucial. Strategic partnerships, diversification of property portfolios, and focus on meeting evolving consumer preferences (sustainability, location, smart home features) will be key to success in this competitive environment. Analyzing regional variations in demand and supply is critical for targeted investment decisions. Given the considerable market size and consistent growth projections, the French residential real estate sector is poised for continued expansion throughout the forecast period, making it an attractive market for both domestic and international players. Recent developments include: January-2022: Nexity (a major integrated real estate group) and Meridiam (a purpose company specializing in sustainable infrastructure) partnered to support local authorities in the rehabilitation of city centers in France. This partnership supports major urban projects to rehabilitate run-down housing, clean up infrastructure (buildings and housing, etc.), and conduct urban renewal operations., June-2021: Fnac Darty (leading omnichannel player in Europe) and Nexity (a major integrated real estate group) entered a commercial partnership to meet their consumers' needs by combining their respective expertise and shared values of proximity, service quality, and accessibility.. Key drivers for this market are: Green And Sustainable Buildings Initiatives, Urbanisation and Tousrism Growth. Potential restraints include: Decliing Crude Oil Prices. Notable trends are: Detached Home Sales are Witnessing Lucrative Growth.

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.

🚀 Welcome to Godi.AI's Predictive Analysis of IFI Tax for French Cities

Hello, business innovator! 🌎 I'm Santiago PATINO SERNA, the CEO and data scientist at Godi.AI. This notebook presents the data reading and processing steps (for a detailed explanation, please refer to this other Notebook on Github). We delve into feature engineering followed by the development of six unique models. Each model's hyperparameters are optimized automatically. Following this, we evaluate each model's performance using cross-validation. With the results in hand, Generative AI steps in to assess the models. Acting as an expert data scientist, Generative AI determines the optimal model for deployment, explaining its selection in depth.

📊 Notebook Overview

Notebook on Github

Predictive Analysis of IFI Tax for French Cities

• Data Loading: Initializing necessary libraries and importing the IFI tax dataset.
• Feature Engineering: Transforming raw data into informative features to enhance model performance.
• Model Development: Creating six unique models, each with automated hyperparameter optimization.
• Performance Evaluation: Assessing each model's predictive capability using cross-validation techniques.

Generative AI Model Analysis

Delve into: - Comparative analysis of all models' performance. - Generative AI's role as an expert data scientist in selecting the optimal model. - A detailed explanation of the chosen model and its implications for deployment.

📸 Key Visual Insights

https://drive.google.com/uc?export=view&id=1AYVkEcBwaNRV7SYe3b4NVvB4GZAxTamA" alt="Pair Plot of Feature Engineering variable">
Analysis of the RAW variables plus the feature-engineered ones. In this image, variables have been cleaned of outliers and normalized.

https://drive.google.com/uc?export=view&id=1AYZxrO84QWsuCw3qU2kv9Z0kxclMNCQS" alt="KDE of the Predictable Variable Y">
KDE analysis to view the distribution of the predictable Y variable, equivalent to the number of tax payers multiplied by the average tax for each city. This variable has been normalized and is without outliers.

https://drive.google.com/uc?export=view&id=1AiKaGMoQ7V1PF4QgQZXDHBL_vGGMxe0y" alt="Results of the different tested models">
Numerical analysis of various metrics across all models to select the optimal one.

https://drive.google.com/uc?export=view&id=1Ahiym3e69XDaTOqpktqRGYhHawW5v_ks" alt="AI Analysis to select the best model">
This shows the AI's analysis of the previous chart to select the best model.

https://drive.google.com/uc?export=view&id=1AbNa3WRHvWRkZo_czA6L5Rl8ZQkPLjKh" alt="Results XGboost model"> Results of the model selected by the generative AI as the best.

https://drive.google.com/uc?export=view&id=1AlAF2HVU3I0YDkyI6WdrGF3mdJP6M2vq" alt="Graphical representation of the best predictive model selected by GEN AI"> Graphical results of all models, compared to the best one selected by the AI.

🤖 About Godi.AI

Godi.AI is the startup reshaping how businesses experience AI. We focus on speed, ROI, and guiding businesses on their digitalization journey. Dive into our standout apps, or explore tailored solutions with our Godi.AI Freelancer method.

Special Note: For businesses seeking an even more customized experience, reach out to me directly. As a proud Polytechnique Paris graduate, I am here to turn your data into insightful, actionable decisions.

📩 Get Started: Ready to embark on this transformative journey with Godi.AI? Reach out to us!

📔 Explore the Notebook: For a detailed dive, explore the Notebook in Github on GitHub.