scikit-mobility is a library for human mobility analysis in Python. The library allows to:

  • represent trajectories and mobility flows with proper data structures, TrajDataFrame and FlowDataFrame.

  • manage and manipulate mobility data of various formats (call detail records, GPS data, data from Location Based Social Networks, survey data, etc.);

  • extract human mobility metrics and patterns from data, both at individual and collective level (e.g., length of displacements, characteristic distance, origin-destination matrix, etc.)

  • generate synthetic individual trajectories using standard mathematical models (random walk models, exploration and preferential return model, etc.)

  • generate synthetic mobility flows using standard migration models (gravity model, radiation model, etc.)

  • assess the privacy risk associated with a mobility dataset



Full instructions to install the library are available in the scikit-mobilty repository.

Installation with pip (python >= 3.7 required)

  1. Create an environment skmob

    python3 -m venv skmob
  2. Activate

    source skmob/bin/activate
  3. Install skmob

    pip install scikit-mobility
  4. OPTIONAL to use scikit-mobility on the jupyter notebook

Activate the virutalenv:

source skmob/bin/activate

Install jupyter notebook:

pip install jupyter

Run jupyter notebook

jupyter notebook

(Optional) install the kernel with a specific name

ipython kernel install --user --name=skmob

Installation with conda - miniconda

  1. Create an environment skmob and install pip

    conda create -n skmob pip python=3.7 rtree
  2. Activate

    conda activate skmob
  3. Install skmob

    conda install -c conda-forge scikit-mobility
  4. OPTIONAL to use scikit-mobility on the jupyter notebook

Install the kernel

conda install jupyter -c conda-forge

Open a notebook and check if the kernel skmob is on the kernel list. If not, run the following:

On Mac and Linux

env=$(basename `echo $CONDA_PREFIX`)
python -m ipykernel install --user --name "$env" --display-name "Python [conda env:"$env"]"

On Windows

You may run into dependency issues if you try to import the package in Python. If so, try installing the following packages as followed.

conda install -n skmob pyproj urllib3 chardet markupsafe

Known Issues

the installation of package rtree could not work with pip within a conda environment. If so, try

pip install "rtree>=0.8,<0.9"

or install rtree with conda

conda install rtree


scikit-mobility is an ongoing open-source project created by the research community. The library is in its first BETA release, as well as the documentation. In the case you find errors, or you simply have suggestions, please open an issue in the repository. We would love to hear from you!