Overview:
This project is to explore data relate to the US Bikeshare program run by Motivate. Their mission is to revolutionize the landscape of cities by making them more "accessible, healthier, and sustainable."
The analysis will look at three major cities and the available trip data riders take between stations. The analysis will look at rider trip information like length of trip, starting station and ending station. Other information will be used when available like rider gender and birth year.
Datasets available are randomly selected from January through June of 2017. The cities include Chicago, New York City, and Washington. Information was provided in three separate CSV file sets (See below).
Information included in files: Start Time End Time Trip Duration in Seconds Start Station End Station User Type Gender Birth Year
Note: Gender and Birth Year were not available for all cities.
Software used: Anaconda3
Files: bikeshare.py chicago.csv
Resources Python documentation
Time_Stats Month, Day, and Hour Frequency Usage
Station_Stats Most Frequent Starting Station Most Frequent Ending Station Most Frequent Start and End Station Combination Top 5 Frequently Used Station Start and End Combinations along with Trip Counts Total Trips Made in Data Set
Trip_Duration Total city-wide trips Total City Trip Duration (mins. and secs.) Mean Duration Per Trip (mins. and secs.)
User_Stats (Where Available) Summary of User Genders (count) Male vs Female ratio (percentage) Most Frequently Selected Birth Year Oldest Selected Birth Year Youngest Selected Birth Year
Raw_Data Provides Rows of Raw Data from city file if requested. In 5 row increments until user continues.
