Bike-sharing project for Cyclistic, a fictional company
Bike-sharing project for Cyclistic, a fictional company
Embedded Files
Tools used: Excel, R, and Tableau
Tools used: Excel, R, and Tableau
My approach to the project
Read the csv files for May, June, July, and August
Merge them to one file and saved as a data frame
Clean and prep data in R
Remove unwanted columns
Make date format consistent
Find duplicates: No duplicates found
Find and remove any rows that is empty or has all NA values
Store the result in a different data frame each time
Add columns in R
Add columns ride_length
Enter NULL for all NA values
Remove negative values for ride_length
Export to csv file for further analysis in R
Export the resultant data frame to csv file
Import the csv file and calculate day_of_week field in Tableau
Create visualizations and prepare a project report with visuals and recommendations
About the visualizations
The following visualizations were created using Tableau to perform analysis of Cyclistic's (a fictious company) bike-sharing program. There are two types of riders here: casual riders and members. The main objective of this project is to identify areas and steps that can convert casual riders to members.
The visualizations show that as far as months are considered, June and July have the highest volume of riders and ride lengths are longer during these months. As far as days are considered, weekends are most suitable due to the same reason. Looking at the rideable types, the segment to be looked at is docked bikes that have riders with longer ride lengths.
Conclusion and recommendations
To begin with a positive note, the number of members is already larger compared to casual riders.
Average ride length of casual riders is high and it indicates that individual casual riders who have the longest ride lengths could be approached for being a member.
Looking at the month-wise data, we can see that June-July timeline has the highest volume, and July has the longest ride length for casual riders. We can find potential members during this time frame.
Weekends are other suitable days to approach people who can be potential members, as the count and ride length is comparatively larger.
Another segment to look at is docked bikes and provide them favors like discount, as they have the maximum ride length contribution among all three rideable types.
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