The objective of the project is to build a model that can predict the number of bike share stations that should be created in zip codes that surround a company’s current network of bike stations. They could then use the model as a guide for an expansion effort.
Compared difference among bike users of Jersey City based on stations, gender and season in 2019.
Application web interactive permettant de localiser et de récupérer des données en temps réel sur les stations de vélos partagés à Lille, Toulouse et Strasbourg. Fonctionnalités : carte interactive, recherche GPS et mises à jour en temps réel.
Finding bikes for the Bay Area bikeshare program
Statistical Modelling using Python of CityBikeAPI Data
Aggregate the data found in the New York Citi Bike Trip History Logs and find two unexpected phenomena using Tableau.
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