bike-sharing
Data Collection
src/data-preprocessing
API requests to receive all current locations of bikes from nextbike, lidlbike and mobike in Berlin (inner circle) and store them into a single database.
Add config.py file to src/ with API Keys for Deutsche Bahn API (https://developer.deutschebahn.com/store/) and database credentials.
For access to lime bike API insert phone_no to config.py and follow steps in lime_access.py (three manual steps required).
Other open data on bikes system can be accessed on https://github.com/Liyubov/tidytuesday/tree/master/data/2019/2019-04-02
Data Analysis
src/analysis
Jupyter Notebook to analyse data.
-
preprocess.ipynb contains the preprossing steps of the raw data to a usable format.
- raw.csv contains the data from the database
- preprocessed.csv contains the data with added columns and fixed lat / lng
- routed.csv contains the data with distance and waypoints
- cleaned.csv is the cleaned routed dataset (unplausible data is removed)
- pseudonomysed.csv is the anonymized, cleaned data, following this standard
- pseudonomysed_raw.csv ist the anonymized data (NOT cleaned).
-
analysis.ipynb includes analysis about provider and bike specific data
-
pseudonomysed.ipynb includes analysis using the anonymized dataset (without information on providers.)
In folder bike analysis trajectories we analyze bikes trajectories (work in progress).
Jupyter Notebook data analysis
- analysis of trajectories is described in bikes_mobility_analysis_trajectories folder