Bike Rental Insights Dashboard
A Streamlit dashboard on how weather, season and working days shape bike rentals, with an RFM analysis.
- Status
- Status: CompletedFinished and delivered. It does what it set out to do and no more work is planned.
- Kind
- Dashboard
- Started
- Jul 2025
- Updated
- Oct 2026
About it
The problem
A rental business cannot plan its fleet or pricing without knowing how demand moves with the weather and the calendar.
The approach
This is my submission for Dicoding's Data Analysis with Python course. I analysed the Bike Sharing dataset in a notebook, then published the findings as a Streamlit dashboard.
- Rentals compared across seasons to find the most and least popular.
- The relationship between weather conditions and total rentals.
- Working days compared with weekends and holidays, and an RFM analysis.
The result
A small, clear dashboard that turns the dataset into answers about when and why people rent. The notebook and the dashboard are both in the repository.
What it does4
Season Trends
Weather Impact
Working Days and Holidays
RFM Analysis
More work
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