- Fri 17 December 2021
- data
- #cycling-in-marburg
This blog article accompanies my oral rC3 2021 contribution “Optimising public transport: A data-driven bike-sharing study in Marburg”.
Table of Contents:
Video
(to be added.)
Blog posts on 2020 data only
- Cycling in Marburg (1/4): Project introduction and data source
- Cycling in Marburg (2/4): For Nextbike users
- Cycling in Marburg (3/4): For the city council
- Cycling in Marburg (4/4): Machine learning predictions
- Cycling in Marburg: Cycling in Marburg: Interactive transition matrix figures
Figures
Every figure can be clicked on.
Day-hour histogram.
Probability to find a station emtpy.
Probability to find a station empty against its mean occupation number.
Parked bikes against time.
Transition matrix with diagonal elements.
Transition matrix without diagonal elements.
Popular routes.
Corona comparison.
Number of bike stations and number of bikes in Marburg.
Number of trips.
Traveled distance.
Kcal burned.
Ecological benefits.