Check out my full report here!
I completed this case study as the capstone project for the Google Data Analytics Certification course. I used base R and tidyverse to complete my analysis and create visualizations.
The case study is about Chicago's Divvy bike-share, and my objective is evaluate how members and non-members ("casual") use the bike-share differently. I analyzed the duration of user trips, the locations of these trips, and the types of bikes used.
The data is taken from a real bike-share -- Chicago-based Divvy -- but in the original case study my objective was set for a fictional company. Because there were some differences between Divvy and the fictional Cyclistic bike-share, I decided to conduct this analysis as if I were conducting this analysis for Divvy.
For analysis:
- tidyverse (inc. dplyr, ggplot2)
- lubridate
- kableExtra