Historical dataset of population level and growth rate for the Bordeaux, France metro area from 1950 to 2025.

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

Cette statistique présente l'évolution du nombre de personnes vivant à Bordeaux depuis 1968, jusqu'en 2020. La population bordelaise a fortement diminué entre 1968 et 1982, puis la croissance démographique est revenus dans les années 90. En 2020, la ville compte près de 260.000 habitants.

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

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

Ce jeu de données contient des informations sur l’évolution de la population du territoire de Bordeaux Métropole pour chaque recensement depuis 2007 (2007, 2012, 2017). Les variables proposées par l’INSEE recouvrent des catégories démographiques liées à l’âge des individus, à leur sexe, à leur catégorie socio-professionnelle et à leur ancrage géographique. Enrichissements - ajout des hiérarchies administratives (EPCI, département, région) sur la base de la géographie en 2020, - ajout des noms de variables INSEE en complément des codes des variables.

Ce graphique indique le nombre d'habitants de la ville de Bordeaux en France en 2014, par sexe. Cette année là, près de ******* hommes vivaient à Bordeaux.

According to a survey conducted in early 2018, half of the surveyed French declared using the bike as a mean of transportation. However, ** percent of them said to bike less than once a month and only **** percent used the bicycle daily or almost daily as their transportation.  The vast majority of French surveyed by the French bicycle touring federation declared taking a bike for leisure activities, while almost a third said using it as a mean of transportation.

Usage of bicycles in city areas in France

Strasbourg, Grenoble and Bordeaux were the cities with the highest percentage of employees who used the bike to go to work in France in 2015 : in these metropoles between ** and ** percent of the working population went to work cycling. In Paris only **** percent of employees did so. This ratio appears to be more important when people commute within city-centers or big cities, which would be linked to the presence of better cycling infrastructures.

Overall bicycle mobility goals in France

On the observation that daily bike use represents only ***** percent of all daily travels, the French government stressed in September 2018 a “Plan Vélo” (Bicycle Plan). This to increase the bicycle mobility until 2024, along with the goal of ensuring security and to better cycling infrastructures. most of French bike users seemed to still feel unsecure when cycling in cities in a survey conducted in 2017.

répartition par catégories socioprofessionnelles de la population de Bordeaux

Objective The aim of this study was to develop an accurate regional forecast algorithm to predict the number of hospitalized patients and to assess the benefit of the Electronic Health Records (EHR) information to perform those predictions. Materials and Methods Aggregated data from SARS-CoV-2 and weather public database and data warehouse of the Bordeaux hospital were extracted from May 16, 2020, to January 17, 2022. The outcomes were the number of hospitalized patients in the Bordeaux Hospital at 7 and 14 days. We compared the performance of different data sources, feature engineering, and machine learning models. Results During the period of 88 weeks, 2561 hospitalizations due to COVID-19 were recorded at the Bordeaux Hospital. The model achieving the best performance was an elastic-net penalized linear regression using all available data with a median relative error at 7 and 14 days of 0.136 [0.063; 0.223] and 0.198 [0.105; 0.302] hospitalizations, respectively. Electronic health records (EHRs) from the hospital data warehouse improved median relative error at 7 and 14 days by 10.9% and 19.8%, respectively. Graphical evaluation showed remaining forecast error was mainly due to delay in slope shift detection. Discussion Forecast models showed overall good performance both at 7 and 14 days which was improved by the addition of the data from Bordeaux Hospital data warehouse. Conclusions The development of hospital data warehouses might help to get more specific and faster information than traditional surveillance systems, which in turn will help to improve epidemic forecasting at a larger and finer scale. Methods Aggregated data from 2020-05-16 to 2022-01-17 regarding Bordeaux Hospital EHR. Bordeaux hospital data warehouse was used, during the pandemic, to describe the current state of the epidemic at the hospital level on a daily basis. Those data were then used in the forecast model including: hospitalizations, hospital and ICU admission and discharge, ambulance service notes and emergency unit notes. Concepts related to COVID-19 were extracted from notes by dictionary-based approaches (e.g. cough, dyspnoea, covid-19). Dictionaries were manually created based on manual chart review to identify terms used by practitioners. Then, the number and proportion of ambulance service calls or hospitalization in emergency units mentioning concepts related to covid-19 were extracted. Due to different data acquisition mechanisms, there was a delay between the occurrence of events and the data acquisition. It was of 1 day for EHR data, 5 days for department hospitalizations and RT-PCR, 4 days for weather, 2 days for variants and 4 days for vaccination. For the training and evaluation of the model, the chosen date was the date of data availability to mimic a real-time streaming forecast.

Genomic offset models are increasingly popular tools for identifying populations at risk of maladaptation under climate change. These models estimate the extent of genetic change required for populations to remain adapted under future climate change scenarios, but face strong limitations and still lack broad empirical testing. Using 9,817 single nucleotide polymorphisms (SNPs) genotyped in 454 trees from 34 populations of maritime pine, a species with a marked population genetic structure, we found substantial variability across genomic offset predictions from different methods, SNP sets, and general circulation models. Using five common gardens, we mostly found positive associations between genomic offset predictions and mortality, as expected. However, contrary to our expectations, we observed very few negative monotonic associations between genomic offset predictions and height. Higher mortality rates were also observed in national forest inventory plots with high genomic offset, but..., , , # Data and code for the paper: Evaluating genomic offset predictions in a forest tree with high population genetic structure

Juliette Archambeau^1,2, Marta Benito-Garzón¹, Marina de-Miguel^1,3, Alexandre Changenet¹, Francesca Bagnoli⁴, Frédéric Barraquand⁵, Maurizio Marchi⁴, Giovanni G. Vendramin⁴, Stephen Cavers², Annika Perry² and Santiago C. González-MartÃnez¹

1 INRAE, Univ. Bordeaux, BIOGECO, F-33610 Cestas, France

2 UK Centre for Ecology & Hydrology, Bush Estate, Penicuik, United Kingdom

3 EGFV, Univ. Bordeaux, Bordeaux Sciences Agro, INRAE, ISVV, F-33882, Villenave d'Ornon, France

4 Institute of Biosciences and BioResources, National Research Council, 50019 Sesto Fiorentino, Italy

5 CNRS, Institute of Mathematics of Bordeaux, F-33400 Talence, France

Corresponding author: Juliette Archambeau, [juli.archambeau@gmail.com](mailto:juli.ar...,

A process of adaptive divergence for tolerance to high temperatures was identified by using a rare model-system, consisting of two sympatric populations of a Lepidoptera (Thaumetopoea pityocampa) with different life-cycle timings, a "mutant" population with summer larval development, Leiria SP, and the founder natural population, having winter larval development, Leiria WP. A third, allopatric population (Bordeaux WP) was also studied. First and second instar larvae were experimentally exposed to daily-cycles of heat treatment reaching maximum values of 36, 38, 40 and 42ºC; control groups placed at 25ºC. A lethal temperature effect was only significant at 42ºC, for Leiria SP, whereas all temperatures tested had a significant negative effect upon Leiria WP, thus indicating an upper threshold of survival c.a. 6ºC above that of the WP. Cox regression model, for pooled heat treatments, predicted mortality hazard to increase for Leiria WP (+108%) and Bordeaux WP (+78%) in contrast with Leiri...

répartition par catégories socioprofessionnelles de la population d'Artigues-près-Bordeaux

répartition par catégories socioprofessionnelles de la population de Carignan-de-Bordeaux

Les données représentées ici, révèlent que le taux de chômage varie sensiblement d'une zone à l’autre. On distingue très clairement ou sont les zones les plus touchées. Dans cette carte, les zones avec le plus fort taux sont celles ou le chômage touche plus de 25% de la population active. Celles à très fort taux représentent un chômage touchant plus de 15% de la population active. Le fort taux est au-delà de 10% de la population active. Les dernières catégories sont à 7,5% de la population active, et 5% de la population active.

Les données utilisées proviennent du produit FranceIRIS® développé par Esri France, les informations sur le taux de chômage sont de 2011.

répartition par catégories socioprofessionnelles de la population de Saint-Caprais-de-Bordeaux

Cette carte représente la proportion des plus de 65 ans. C'est à dire le rapport entre la population des plus de 65 ans et la population totale. On distingue très clairement les zones où la proportion des plus de 65 ans est la plus importante (en jaune). Les données utilisées proviennent du produit FranceIRIS® développé par Esri France.

Characteristics of the study population—Comparison between drivers responsible and not responsible for the road crash (n = 954).

répartition par catégories socioprofessionnelles de la population de Lignan-de-Bordeaux

During the first quarter of 2025, La Réunion and Guyane, two overseas regions, had the highest unemployment rate among all French regions. Over there, the unemployment rate reached **** and **** percent, respectively, compared to around *** percent in Bretagne and Pays de la Loire. Unemployment: an important issue in the economy of France France has been struggling with unemployment since the end of the 2000s and the beginning of the 2008 financial crisis. The unemployment rate in the country reached a record level in 2015 when it amounted to nearly **** percent. However, the situation of employment in France has shown signs of recovery since then. Youth unemployment in the country is finally decreasing; in the meantime, long-term unemployment in France has not yet regained its pre-2008 levels, but stood at *** percent in 2024, a decrease of *** points since the previous year. Being unemployed in France Unemployment does not affect the population in the same way. As displayed by this figure, the northern part of France, which used to be a mining center, was more impacted by the phenomenon. Workers, contrary to the more qualified socio-professional categories, were also more affected by unemployment, as well as women, who are usually more unemployed than men in France, regardless of their nationality.