Focusing on human mobility data, trackintel provides functionalities for data quality enhancement, integrating data from various sources, performing quantitative analysis and mining tasks, and visualizing the data and/or analysis results. In addition to these core functionalities, packages are provided for user mobility profiling and trajectory-based learning analytics.
You can find the documentation on the trackintel documentation page.
trackintel is intended for use mainly by researchers with:
- Programming experience in Python
- Proficiency in movement data mining and analysis
- Movement data exists in csv, (geo)json, gpx or PostGIS format
- Movement data consists of points with x,y-coordinates, a time stamp, an optional accuracy and a user ID
- The tracking data can be reasonably segmented into
- positionfixes (raw tracking points)
- triplegs (aggregated tracking points based on the transport mode)
- trips (aggregated activities based on the visited destination / staypoint)
- tours (aggregated trips starting / ending at the same location / staypoint)
- One of the following transportation modes was used at any time: car, walking, bike, bus, tram, train, plane, ship, e-car, e-bike
This is not on pypi.org yet, so to install you have to git clone the repository and install it with pip install ..
You should then be able to run the examples in the examples folder or import trackintel using:
import trackintel
You can install trackintel locally using pip install .. For quick testing, use trackintel.print_version().
Testing is done using pytest. Simply run the tests using pytest in the top-level trackintel folder.
The documentation follws the pandas resp. numpy docstring standard. In particular, it uses Sphinx to create the documentation.
You can install Sphinx using pip install -U sphinx or conda install sphinx. Generate the documentation using python make.py in the doc folder. Attention! This will copy the generated HTML to a folder trackintel-docs (containing the documentation repository https://github.com/mie-lab/trackintel-docs), which must exist in parallel to this repository. After copying, you can push the other repository to update the documentation.
trackintel is primarily maintained by the Mobility Information Engineering Lab at ETH Zurich (mie-lab.ethz.ch). If you want to contribute, send a pull request and put yourself in the AUTHORS.md file.