This graph shows the number of inhabitants of the city of Saint-Denis in France in 2017, by gender. That year, almost 57,000 males were living in Saint-Denis, slightly more than the number of females.

2011 census of licenses from sports federations approved by the ministry in charge of sports.
The data set presents by city and by federation: the number of licensees in Seine-Saint-Denis, women, less 20 years old, over 60 years old, Insee population data.
The data is geocoded (municipalities).
(Source Ministry of Sports, 23 Sept. 2013)

Ce graphique indique le nombre d'habitants de la ville de Saint-Denis en France en 2014, par sexe. Cette année là, plus de ****** hommes vivaient dans la la ville de Saint-Denis.

répartition par catégories socioprofessionnelles de la population de la Seine-Saint-Denis

This graph shows the distribution of immigrants in French departments in 2021. It reveals that Seine-Saint-Denis was the department with the highest proportion of immigrants. Nearly a third of its population was composed of immigrated residents.

répartition par catégories socioprofessionnelles de la population de Saint-Denis-en-Val

répartition par catégories socioprofessionnelles de la population de Saint-Denis-de-Méré

répartition par catégories socioprofessionnelles de la population de Saint-Denis-de-Palin

répartition par catégories socioprofessionnelles de la population d'Estrées-Saint-Denis

Characteristics of immigrant PLWHIV compared to those born in France, 2021, Seine-Saint-Denis, France.

Acceptability of the COVID-19 vaccine among immigrant participants compared to those born in France, 2021, Seine-Saint-Denis, France.

M-POPP datasets This repository contains 2 datasets created within the EXO-POPP project (Optical EXtraction of handwritten named entities for marriage records of the POPulation of Paris) for the task of text recognition and information extraction. These datasets have been published in End-to-end information extraction in handwritten documents: Understanding Paris marriage records from 1880 to 1940 [1]at ICDAR 2024. This version contains the labels for Handwritten Text Recognition and Handwritten Text Recognition + Information Extraction as used in our new paper "DANIEL: A fast Document Attention Network for Information Extraction and Labelling of handwritten documents" [3]. This version makes corrections to the handwritten dataset. More precisely, it corrects a few errors in transcription annotations and named entities. The printed dataset is unchanged compared to version 2. The performances of the models described in [1] and [3] are detailled in the Leaderboard section. General information The EXO-POPP project aims to establish a comprehensive database comprising 300,000 marriage records from Paris and its suburbs, spanning the years 1880 to 1940, which are preserved in over 130,000 scans of double pages. Each marriage record may encompass up to 118 distinct types of information that require extraction from plain text. The M-POPP corpus (which stands for Marriage records of the POPulation of Paris) is the corpus on which the EXO-POPP project focuses. This corpus was built by gathering the marriage records of Paris and its suburb regions (Hauts- de-Seine, Seine-Saint-Denis, Val-de-Marne). The M-POPP corpus are a subset of the M-POPP database with annotations for full-page text recognition and named entity recognition/information extraction from both handwritten and printed documents. The first dataset comprises handwritten marriage records, while the second dataset consists of typewritten marriage records. It should be noted that even in typewritten marriage records, some handwritten information occurs, especially concerning the names of the spouses, and notes in the margin.The dataset contains single-page images obtained from the original scans of double pages via page segmentation. The structure of the files is the following: handwritten: the handwritten dataset images: images of the dataset divided following the split used in [1] train valid test labels: labels for joint handwritten text recognition and information extraction for each encoding tested in [1] printed: the printed dataset images: images of the dataset divided following the split used in [1] train valid test labels: labels for joint handwritten text recognition and information extraction for each encoding tested in [1] encoding-2-to-encoding-5.json: a JSON file giving the correspondence between the symbols of encoding 2 and encoding 5. Table 1: Details on the split of the handwritten dataset. Train Validation Test Pages 250 32 32 Acts 344 51 53 Named entities 16727 2223 2517 Table 2: Details on the split of the printed dataset. Train Validation Test Pages 116 14 13 Acts 363 43 30 Named entities 22036 2559 2405 Table 3: Average annotation statistics per act for the two M-POPP datasets. Dataset # of characters # of words # of named entities Handwritten 1519 231 48 Printed 1328 200 60 Document structure Annotation We employ the procedure applied in [2], which involves adding opening and closing tags to the character set for each text block we want to recognize.In total, we define four types of text blocks. Block A is located in the margin and contains the last names of the married couple, possibly with their first names and the date of the marriage. Block B is the body of the text. Block B is the one that contains most of the information to be extracted. Block C is optional and corresponds to marginal notes used in various cases, such as the mention of a divorce or a correction made to the act. Block D corresponds to a set containing a block A and a block B, optionally with one or more blocks C. Information Extraction annotation The dataset contains 118 information categories. As explained in the paper, we broke down the named entities into sub-elements pertaining to 4 hierarchical levels, which reduces the total number of categories to 23 instead of 118. Notice that level 1, 2, and 3 categories do not encode named entities but rather the relations that may occur between some lower level categories for example: (day, birth, husband) encodes the fact that the annotated piece of text is the date of birth of the husband. For these datasets, we chose to represent these hierarchical elements with emojis. For instance, the information first name is represented by the emoji 💬.The meaning of each emoji can be found in Table 4. To determine the best way to encode named entities in the ground truth, we compared in [1] 5 types of encoding. To illustrate these encodings, let’s take for instance Louis Alexandr...

répartition par catégories socioprofessionnelles de la population de Sauveterre-Saint-Denis

Localisation des équipements pour personnes âgées à Montreuil. Données issues des tableaux de bord du Secteur des Équipements pour Personnes Âgées du Service de la population âgée du Département de Seine-Saint-Denis, réalisées à partir du recensement des établissements médico-sociaux pour personnes âgées existants ou à venir sur le territoire de la Seine-Saint-Denis.

Patient characteristics by acceptability of the COVID-19 vaccine, Seine-Saint-Denis, 2021 (multinomial model).

Ce graphique présente le classement des villes ayant le plus d'habitants en France en 2021. Paris était la ville plus peuplée de France, la capitale comptait plus de deux millions de personnes, soit plus du double que Marseille, deuxième ville de France. Saint-Denis (La Réunion) était la ville la plus importante des territoires et départements d'outre-mer. Ces données ne prennent en compte que la population des communes et non les habitants des aires urbaines.

aubervilliers categories-socio-professionnelles csp deces densite emploi-chomage epinay ept etablissement ile-saint-denis la-courneuve logement menage-famille naissance pierrefitte plaine-commune population revenu-pauvrete saint-denis saint-ouen-sur-seine scolarite-diplomes stains superficie villetaneuse voiture

Les villes du département de la Réunion étaient les plus touchées par la pauvreté en France en 2017. Cette année-là, près de la moitié de la population des villes de Saint-Benoît, Saint-Louis, Saint-André, Saint Joseph et Le Port vivait sous le seuil de pauvreté fixé à 60 % du revenu médian. Les villes de Seine-Saint-Denis sont également très touchées par la précarité et les revenus faibles. Parmi ce classement des 20 villes au taux de pauvreté le plus élevé, sept se trouvent dans ce département de la petite couronne.

Cette statistique représente la part de la population de chaque département français que représentent les immigrés en 2021. Le département enregistrant la part d'immigrée la plus importante dans sa population était la Seine-Saint-Denis, à l'opposé, le Pas-de-Calais et la Réunion étaient les départements avec le moins d'immigrés proportionnellement.

Cette statistique présente la part de la population sous le seuil de pauvreté monétaire en France en 2021, selon le département. L'INSEE enregistre une importante fracture de richesse entre les départements métropolitains et ceux d'outre-mer. La Guadeloupe, la Réunion, la Guyane et Mayotte sont les départements français avec le taux de pauvreté le plus élevé du pays. Le taux maximum en France métropolitaine était atteint par la Seine-Saint-Denis, qui possédait un taux supérieur à celui de la Martinique.