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The Paris 2024 Olympic Summer Games dataset provides comprehensive information about the Summer Olympics held in 2024. It covers various aspects of the event, including participating countries, athletes, sports disciplines, medal standings, and key event details. More about the Olympic Games on the official site Olympics Paris 2024 and Wiki.

Dataset Structure

Related Datasets

• Paralympic Summer Games Paris 2024 & Tokyo 2020
• Olympic Games, 1986-2022
• Horses - Olympic Equestrian
• Beijing 2022 Olympic Winter Games
• Tokyo 2020 Olympic Summer Games
• Olympic Games Hosts

ACKNOWLEDGMENT

I am very thankful to Luca Fontana, zenzombie and others for their efforts in helping me to make the dataset better. Luca Fontana did a manual check medalist.csv table and zenzombie cover dataset with tests.

Q&A

If you have any questions or suggestions please start a discussion.

The Paris Data Center Market report segments the industry into DC Size (Small, Medium, Large, Massive, Mega), Tier Type (Tier 1 & 2, Tier 3, Tier 4), and Absorption (Utilized, Non-Utilized). It includes historical data and market forecasts for five years.

This database contains the Paris and HCP datasets used in Marrelec et al. (2016). It includes the following files:* empirical_Paris.mat: preprocessed resting-state fMRI time series (TS) and associated diffusion MRI structural connectivity matrices (MAP) for 21 subjects from Paris using the Freesurfer parcellation. The healthy volunteers (right-handed) were recruited within Paris local community. All participants gave written informed consent and the protocol was approved by the local ethics committee. Data were acquired using a 3T Siemens Trio TIM MRI scanner (CENIR, Paris, France). Resting-state fMRI series were recorded during ~11 minutes with a repetition time (TR) of 3.29 s.* empirical_HCP: preprocessed resting-state fMRI time series (TS) and associated diffusion MRI structural connectivity matrices (MAP) for 40 subjects from the Human Connectome Porject (HCP) using the Freesurfer parcellation. Data from healthy, unrelated adults were obtained from the second quarter release (Q2, June 2013) of the HCP database (http://www.humanconnectome.org/documentation/Q2/). Data were collected on a custom 3T Siemens Skyra MRI scanner (Washington University, Saint Louis, United States). Resting-state fMRI data were acquired in four runs of approximately 15 minutes each with a TR of 0.72 s. The four runs were concatenated in time.* freesurferlabels.txt: Freesurfer labels of the 160 regions used for the parcellation.* simulations_individuals_Paris.mat: simulated functional connectivity (FC) matrices generated using an abstract model of brain activity (the SAR model) and simulated resting-state fMRI time series (TS) generated using 6 mainstream computational models of brain activity (models), all using as input the structural connectivity of each individual subject belonging to the Paris dataset. Simulated resting-state fMRI data were simulated during ~8 minutes at a sampling frequency of 2 Hz.* simulations_average_Paris.mat: simulated functional connectivity (FC) matrices generated using an abstract model of brain activity (the SAR model) and simulated resting-state fMRI time series (TS) generated using 6 mainstream computational models of brain activity (models), all using as input the average structural connectivity of all subjects belonging to the Paris dataset. Simulated resting-state fMRI data were simulated during ~8 minutes at a sampling frequency of 2 Hz.* simulations_average_homotopic.mat: simulated functional connectivity (FC) matrices generated using an abstract model of brain activity (the SAR model) and simulated resting-state fMRI time series (TS) generated using 6 mainstream computational models of brain activity (models), all using as input the average structural connectivity of all subjects belonging to the Paris dataset and an artificial addition of homotopic structural connections. Simulated resting-state fMRI data were simulated during ~8 minutes at a sampling frequency of 2 Hz.Reference:Marrelec G, Messé A, Giron A, Rudrauf D (2016) Functional Connectivity’s Degenerate View of Brain Computation. PLoS Comput Biol 12(10): e1005031. doi:10.1371/journal.pcbi.1005031

Scientific discovery can be aided when data is shared following the principles of findability, accessibility, interoperability, reusability (FAIR) data (Wilkinson et al., 2016). Recent discussions in the palaeoclimate literature have focussed on defining the ideal database format for storing data and associated metadata. Here, we highlight an often overlooked primary process in widespread adoption of FAIR data, namely the systematic creation of machine readable data at source (i.e. at the field and laboratory level). We detail a file naming and structuring method that was used at LSCE to store data in text file format in a way that is machine-readable, and also human-friendly to persons of all levels of computer proficiency, thus encouraging the adoption of a machine-readable ethos at the very start of a project. Thanks to the relative simplicity of downcore palaeoclimate data, we demonstrate the power of this simple but powerful file format to function as a basic database in itself: we provide a Matlab-based GUI tool that allows users to search and visualise data by sediment core location, proxy type and species type. The adoption of similarily accessible, machine-readable file formats at other laboratories will promote data sharing within projects, while also allowing for the automation of submission of data to online database repositories with particular formatting and/or metadata requirements, thus reducing post-hoc workload.

Comprehensive dataset containing 60 verified Paris Nails locations in United States with complete contact information, ratings, reviews, and location data.

France Wines: Approved for Circulation: Other Wines: Dept: Paris data was reported at 1.000 hl in Apr 2018. This records a decrease from the previous number of 166.000 hl for Mar 2018. France Wines: Approved for Circulation: Other Wines: Dept: Paris data is updated monthly, averaging 338.000 hl from Aug 2002 (Median) to Apr 2018, with 187 observations. The data reached an all-time high of 1,265.000 hl in Oct 2005 and a record low of 0.000 hl in Feb 2018. France Wines: Approved for Circulation: Other Wines: Dept: Paris data remains active status in CEIC and is reported by General Directorate of Customs and Excise. The data is categorized under Global Database’s France – Table FR.B013: Wine Statistics.

Comprehensive dataset containing 12 verified Paris locations in Argentina with complete contact information, ratings, reviews, and location data.

This dataset contains the Paris subset of the Tourpedia dataset, specifically focusing on points of interest (POIs) categorized as attractions (dataset available at http://tour-pedia.org/download/paris-attraction.csv). The original dataset comprises 4,351 entries that encompass a variety of attractions across Paris, providing details on several attributes for each POI. These attributes include a unique identifier, POI name, category, location information (address), latitude, longitude, specific details, and user-generated reviews. The review fields contain textual feedback from users, aggregated from platforms such as Google Places, Foursquare, and Facebook, offering a qualitative insight into each location.

However, due to the initial dataset's high proportion of incomplete or inconsistently structured entries, a rigorous cleaning process was implemented. This process entailed the removal of erroneous and incomplete data points, ultimately refining the dataset to 477 entries that meet criteria for quality and structural coherence. These selected entries were subjected to further validation to ensure data integrity, enabling a more accurate representation of Paris' attractions.

• Paris.csv It contains columns including a unique identifier, POI name, category, location information (address), latitude, longitude, specific details, and user-generated reviews. Those reviews have been previously retrieved and pre-processed from Google Places, Foursquare, and Facebook, and have different formats: all words, only nouns, nouns + verbs, noun + adjectives and nouns + verbs + adjectives.

• Paris_annotated.csv It contains the ground truth relating to the previous dataset, with manual annotations made by humans on the categorisation of each of the POIs into 12 different pre-defined categories. It has the following columns:

  • POI name
  • POI's address
  • One column for each of the above categories. 1 means that the POI belongs to the category while blank indicates that it does not.

France Wines: Approved for Circulation: AOC & VDQS: Dept: Paris data was reported at 172.000 hl in Apr 2018. This records a decrease from the previous number of 257.000 hl for Mar 2018. France Wines: Approved for Circulation: AOC & VDQS: Dept: Paris data is updated monthly, averaging 86.000 hl from Aug 2002 (Median) to Apr 2018, with 188 observations. The data reached an all-time high of 1,295.000 hl in Aug 2005 and a record low of 5.000 hl in Aug 2003. France Wines: Approved for Circulation: AOC & VDQS: Dept: Paris data remains active status in CEIC and is reported by General Directorate of Customs and Excise. The data is categorized under Global Database’s France – Table FR.B013: Wine Statistics.

Comprehensive dataset containing 10 verified Paris locations in Chile with complete contact information, ratings, reviews, and location data.

Under the current IDBG Corporate Results Framework (CRF) 2020-2023 (https://crf.iadb.org/en), the IDB committed to reach 30% of the total amount approved (including all lending operations) of climate finance during this period. In 2022, the IDB Group - composed of the IDB, IDB Lab (formerly the Multilateral Investment Fund) and IDB Invest - approved US$7.8 billion in climate finance as per the MDB climate finance tracking methodology. This resource is aimed at development activities carried out by the public and private sectors that reduce greenhouse gas (GHG) emissions and thus mitigate climate change, and/or that reduce vulnerability to climate change and contribute to an adaptation process. The IDB only climate finance in 2022 was equivalent to US$ 5.9 billion.

Ami Paris Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Find details of Paris Gourmet Buyer/importer data in US (United States) with product description, price, shipment date, quantity, imported products list, major us ports name, overseas suppliers/exporters name etc. at sear.co.in.

Comprehensive dataset containing 230 verified Paris Baguette locations in United States with complete contact information, ratings, reviews, and location data.

Find details of Paris Foods Corp Buyer/importer data in US (United States) with product description, price, shipment date, quantity, imported products list, major us ports name, overseas suppliers/exporters name etc. at sear.co.in.

Paris Fragrance Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Comprehensive dataset containing 31 verified Paris locations in United States with complete contact information, ratings, reviews, and location data.

.PARIS Whois Database, discover comprehensive ownership details, registration dates, and more for .PARIS TLD with Whois Data Center.

Comprehensive dataset containing 11 verified Paris locations in Morocco with complete contact information, ratings, reviews, and location data.

L’arrondissement municipal désigne une partition de la commune de Paris.Délimitation des arrondissements : le décret impérial du 1er novembre 1859 fixe les dénominations des vingt arrondissements de la ville de Paris. Les communes de Lyon et Marseille présentent également une organisation administrative en arrondissements. Contraintes géographiques et topologiques :Un arrondissement est formé d’un seul polygone. La couche graphique respecte une topologie de surfaces. La cohérence topologique se caractérise par l’absence de « trou » ou de « chevauchement » entre arrondissements.