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La première identifie l'heure de pointe et les quartiers principaux à ces heures de pointes. Le seconde, \n\n## Définitions\n- **Heure de pointe**: Heure à laquelle il y a des fortes concentrations de chauffeurs dans certaines villes\n\n\n## Partie 1: déterminer une heure de pointe par quartier\n\n### Data Loading\n#### fichier Rmd\n- [loadHeetch.Rmd](./workA/loadHeetch.Rmd)\n#### Résumé\n- récupérer \n    - les données des chauffeurs ``heetchmarchcrop.Rds`` (un ``sf`` contient des points) \n    - et la répartition géographique des quartiers de casa ``casaneib.geojson``\n- transformer les données vers une projection correspondant à Casablanca (``crs=26191``)\n- Faire une intersection entre les deux bases de données afin \n- générer un fichier final (``heetchmarchcropwithneib.Rds``) qui contient \n    - les données de ``heetchmarchcrop.Rds`` en projection (``crs=26191``) \n    - le quartier où le point a été retrouvé\n\n\n### Mapping peak hours: Determiner une heure de pointe par quartier\n- les details sont dans le fichier: [task1.Rmd](./workA/main.Rmd) avec une vue [html](./workA/)\n![](res/map.png)\nNombre de points en fonction du quartier\n\n## Partie 2: OD: Determiner les flux \n\n### Task1: OD_jour\n- les details sont dans le fichier: [OD_jour](./workB/rendu/OD_jour.Rmd) avec une vue [html](./workB/rendu/OD_jour.html)\n\n### Task2: OD_week vs week-end\n- les details sont dans le fichier: [OD_week](./workB/rendu/OD_week.Rmd) avec une vue [html](./workB/rendu/OD_week.html)\n\n## Others \n## links\n- https://r-spatial.github.io/sf/articles/sf5.html\n- https://riatelab.github.io/mapsf/reference/mf_map.html","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhermann-web%2Fprojet-rythmes-urbains-heetch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhermann-web%2Fprojet-rythmes-urbains-heetch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhermann-web%2Fprojet-rythmes-urbains-heetch/lists"}