TABLE OF CONTENTS
A clear statement of the
business task
01 A description of all data sources
used
02
Documentation of any cleaning
or manipulation of data
03 A summary of the analysis
04
Supporting visualizations and
key findings
05 Top three recommendations
based on the analysis
06
Home | About | Services | Projects | Contact | Tableau Dashboard | GitHub Used R for Analysis
Documentation of any cleaning or manipulation of data
Below Extra columns are removed from each quarter:
●Q2-2019 ("01 - Rental Details Duration In Seconds Uncapped",
"Member Gender", and "05 - Member Details Member Birthday Year")
●Q3-2019 (birthyear, gender, and tripduration)
●Q4-2019 (birthyear, gender, and tripduration)
●Q1-2020 (start_lat, start_lng, end_lat, end_lng)
Home | About | Services | Projects | Contact | Tableau Dashboard | GitHub Used R for Analysis
Data cleaning and manipulation…
●Renamed columns of each quarter to make them consistent
●Convert ride_id and rideable_type to character so that they can
stack correctly
●Stack quarterly data frames into one big data frame (all_trips)
●Remained columns in all_trips data frame (ride_id, started_at,
ended_at, rideable_type, start_station_id, start_station_name,
end_station_id, end_station_name, and member_casual)
Home | About | Services | Projects | Contact | Tableau Dashboard | GitHub Used R for Analysis
Data cleaning and manipulation…
●Created below columns and derived them from started_at and ended_at
for each ride to make calculation easy, to find trends, patterns, and relations.
●Date
●Month
●Day
●Year
●Ride_length
Home | About | Services | Projects | Contact | Tableau Dashboard | GitHub Used R for Analysis
Summary of the analysis
●Total rides by both members and casual users are 2.54 million
●Overall average ride length is 24 minutes
●Member riders used bikes 79.3% of the time, almost 4 times more than casual
riders (20.7%).
●The average ride length for casual riders is 62 minutes which is 4 times longer
than for annual members which is 14 minutes.
●Workday was the most popular day for annual members to bike, while
weekends were for casual riders. It shows that annual members bike to work.
●For annual members, weekends are the longest ride length, and for casual riders,
weekends are the shortest ride length.
Home | About | Services | Projects | Contact | Tableau Dashboard | GitHub Used R for Analysis
Top three recommendations based on the analysis
●According to the analysis annual member used bikes 4 times more than the casual
riders. This finding helps the marketing team to attract those casual cyclists who will
use bikes more frequently for which annual membership is more cost-effective.
●Workday was the most popular day for annual members to bike, while weekends were
for casual riders. It shows that annual members bike to work. Considering this finding,
the marketing team can offer annual memberships to casual cyclists who use bikes to
commute to work.
●For annual members, weekends are the longest ride length, and for casual riders,
weekends are the shortest ride length. It shows that annual members ride for leisure at
the weekends. Considering this finding, the marketing team can offer casual riders
annual memberships so they can use bikes regularly and lengthier for leisure at the
weekends.
Home | About | Services | Projects | Contact | Tableau Dashboard | GitHub Used R for Analysis
