Trip-History-Analysis

Data Analysis on 'Captial Bikeshare : A bike sharing service in the United States'

For more detailed documentation look into docs/

Instructions to run

(requires python 3+)

1. Install all libraries using(requirements file) : pip3 install -r requirements.txt
2. Run the ui.py file

Screen

Few Notes

The data includes:

• Duration – Duration of trip
• Start Date – Includes start date and time
• End Date – Includes end date and time
• Start Station – Includes starting station name and number
• End Station – Includes ending station name and number
• Bike Number – Includes ID number of bike used for the trip
• Member Type – Indicates whether user was a "registered" member (Annual Member, 30-Day Member or Day Key Member) or a "casual" rider (Single Trip, 24-Hour Pass, 3-Day Pass or 5-Day Pass)

This data has been processed to remove trips that are taken by staff as they service and inspect the system, trips that are taken to/from any of our “test” stations at our warehouses and any trips lasting less than 60 seconds (potentially false starts or users trying to re-dock a bike to ensure it's secure).

NOTE: The 3-Day Membership replaced the 5-Day Membership in Fall 2011

Classification Algo

Classes

1. Registered (member)
2. Casual (casual)

• Logistic Regression
• Naive Bayes
• KNN

Preprocessing

• Selecting duration, station (start and end ids), class (member, casual) (These are the saved models accuracies)

1. KNN accuracy:

   • Custom : 95.15
   • SKLearn : 91.30

2. NB accuracy:

   • Custom : 89.90
   • SKLearn : 91.45

3. LR accuracy:

   • Custom : 88.71
   • SKLearn : 90.17

Directory details

1. processed_dataset/ : processed csv file
2. charts : plots to visualize data
3. lib : custom implementations of all the algos
4. model : saved pre-trained model