2020-07-16
This project uses R to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington.
It imports raw data to answer interesting questions about the data by computing descriptive statistics and making visualizations.
By computing a variety of descriptive statistics, this project provide the following information:
1. Popular times of travel
- most common month
2. Popular stations and trip
- most common start station
3. Trip duration
- average travel time
1. plots of most common month for each city 2. plots of most common start station for each city 3. plots of average travel time for each city
In this project, I used data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns.
The data files used are:
- chicago.csv
- new_york_city.csv
- washington.csv
- RStudio
- Jupyter
- Atom
- Terminal on Mac
- This project is an assignment of Udacity Programming for Data Science with R.
- I was inspired by repo create-your-own-adventure for README writing.