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
