Data Mining and Visualization Analysis of shared bikes ——In the Case of Citi bike

DOI

10.2991/ebmcsr-18.2018.67How to use a DOI?

Keywords

Shared bikes, Data mining, Cycling data, Visualization.

Abstract

As a new kind of sharing economy, shared bikes solve the last kilometer problem of people's travel. This paper analyzes the riding characteristics of shared bike users in New York by using the massive data of shared bikes. Based on the cycling data of Citi Bike, the R language is used to extract, clean and analyze the data, and the analysis results are presented in the form of visualized graphs through data visualization technology. Research shows that the male ratio of Citi bike is high, and users are mainly between 20 and 50 years old; Cycling characteristics are characterized by large differences between workdays and rest days, with morning and evening peaks, and a short period of 0 to 10 minutes; In addition, there is a phenomenon of agglomeration in cycling sites, mostly in areas with high traffic such as railway stations, bus stations and scenic spots.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Can Yang
AU  - Xuemei Li
PY  - 2018/11
DA  - 2018/11
TI  - Data Mining and Visualization Analysis of shared bikes ——In the Case of Citi bike
BT  - Proceedings of the 2018 International Conference on Economics, Business, Management and Corporate Social Responsibility (EBMCSR 2018)
PB  - Atlantis Press
SP  - 346
EP  - 351
SN  - 2352-5428
UR  - https://doi.org/10.2991/ebmcsr-18.2018.67
DO  - 10.2991/ebmcsr-18.2018.67
ID  - Yang2018/11
ER  -