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Simple and effective tools for the analysis of movement data

Project description


Simple and effective tools for the analysis of movement data

Movekit is an open-source software package for the processing and analysis of movement data, including modules for:

  • Data pre-processing (e.g. data checks, smoothing, duplicate removal, interpolation, outlier detection)
  • Feature extraction (e.g. speed, acceleration, heading)
  • Individual-level movement analysis (e.g. autocorrelation, speed distribution, environment exploration)
  • Group-level analysis (e.g. cohesion, polarisation, coordination, leadership)


The easiest way to install movekit is by using pip :

pip install movekit


  • Python >=3.5
  • Pandas (>=0.20.3, <=0.23.4)
  • SciPy (>= 1.3.1)
  • tsfresh (>= 0.12.0)
  • xlrd (>= 1.2.0)
  • seaborn (>= 0.9.0)


You can view a demo of common features in this this Jupyter Notebook.


Movekit Development Status is 2-Pre-Alpha

For an overview of version changes see the CHANGELOG.

Please submit bugs or feature requests to the GitHub issue tracker here.


This package was developed by Eren Cakmak, Arjun Majumdar, and Jolle Jolles from the Data Analysis and Visualization Group and the Department of Collective Behaviour at the University Konstanz, with funding from the DFG Centre of Excellence 2117 "Centre for the Advanced Study of Collective Behaviour" (ID: 422037984).

Released under a GNU General Public License. See the LICENSE file for details.

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