Ford Go Bike Data Anaylsis

by Aly Reda

Dataset

Feb 2019 Ford Bike rides all over CA especially San Francisco.

Summary of Findings

User Type Vs. Gender

1. Male Subscriber having the high rides count

User Type Vs. Gender Vs. Age Group

1. Male Subscrber having the Most Rides specially of group age 20s-30s

Gender Vs. Weekday Vs Duration, Distance and Speed

1. Generally Gender increating by the week end¶

2. Female having the longest Duration riding and Male having the less

3. Others having the lonest distance then Females, it make sense they take more time

4. Both Male and female riding more distance by Thu , Fri and having less distance by the week end

5. Male almost having the faster Speed

6. Male,Female and Others riding slower by the week end

User Type Vs. Weekday Vs Duration, Distance and Speed

1. Customer hacing the longest duration¶

2. Both Riding longer duration by week end

3. Customer hacing the longest distance

4. Both Riding less distance by week end

5. Both Riding slower by the week end

6. Subscriber hacing the higest speed

Age Vs. Weekday Vs Duration, Distance and Speed

1. 10s having slowest riding speed (more time and less distance)

2. 60s having second place duraction with 1st place distance and speed

3. All Duration decreased by the week end except 10s

4. All Speed decreased by the week end except 60s

Key Insights for Presentation

Weekday Distribution

Gender Distribution

Age Distribution

Gender Vs. Weekday Vs Duration, Distance and Speed

Age Vs. Weekday Vs Duration, Distance and Speed