In this second project of GR5243 Applied Data Science, we develop a version 2.0 of an Exploratory Data Analysis and Visualization shiny app regarding citi bikes in New York. See Green Life NYC (focused on mapping) and Citi Bike (focused on routing, although the the functionality did not work as it was tried in September 2018) for the previous works on the same subject.

Term: Fall 2018 Our Citi Bike App

• Team 1

• Team Members:

  • Gabriel Benedict: [email protected]
  • Hongyu Ji: [email protected]
  • Yunfan Li: [email protected]
  • Di Lu: [email protected]
  • Amon Tokoro: [email protected]

• Project summary: Our web app aims at optimizing decision making with regards to the usage of Citi Bike in New York. First, a routing utility is available, that allows users to enter their current location and a destination and be guided as to where to walk to the closest Citi Bike non-empty station and where to drop off at the non-full station closest to destination. Additionally, bike station availability, bike routes, the rain radar, the 3-D histogram representing the frequency of bike usage and the heat map corrspoinding with crime rate on the streets are available to allow users to further refine the routing.

  The data is available at the following links:

  • live Citybike station data
  • NYC bike routes
  • live rain data
  • crime data

• Contribution statement: (default) All team members contributed equally in all stages of this project. All team members approve our work presented in this GitHub repository including this contributions statement.

Following suggestions by RICH FITZJOHN (@richfitz). This folder is orgarnized as follows.

doc/
	proj/
	app/
	lib/
	data/
	figs/
	output/

Please see each subfolder for a README file.