02 Mar 2019

BikeShare Data Analysis

The project specifically calculates key metrics associated with the bikeshare information in 3 cities Chicago, Washington and New York City. The program is very interactive and lets the user filter on the following criteria.

1. City
2. month
3. Day of the week.

It then calculates the following key metrics :

1. Time Stats
2. Most Frequent Times of Travel
3. Most Popular Day of the week
4. Most Popular hour
5. Station Stats
6. Most Popular Station and number of Trips at that stations
7. Most Popular Trip and number of times it is taken
8. Trip Duration Stats
9. Total Trip duration
10. Mean Travel Time
11. User Stats
12. User type and their counts
13. Users by their gender and age

It also does ask the user to view the data of the trips above.

bikeshare_2.py

All the credit goes to the author (sumadikalcha), Udacity training and the student hub.