In this case study, I used a bike-share company data, to identify how annual members and casual riders use bikes differently and to find why casual riders would buy a membership. I was able to suggest action plans based on those findings.
If you want to check this projects in details, visit the Analyzing a bike-shire company for potential growth under Projects section. However if you don’t want to get lost in a long report but still want to check a little more detailed graphs about this dataset, you will find two below:
The first one shows the daily distributions within each month that can be studied for further analysis. (this is to develop the insights that gained in slide no. 6)
- Notice the durations by Casuals in September, compared to other months.
And the second chart below shows the hourly distributions within each month.
- Notice how the Members’ pattern keep being consistent throughout the year, for both the number of trips and their durations. (this is to develop the insights that gained in slide no. 7)
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