What is scikit-mobility?

scikit-mobility is a python library that provides scientists and practitioners with an environment to:

1. load and represent mobility data, both at the individual and the collective level, through easy-to-use data structures
   (TrajDataFrame and FlowDataFrame);
2. visualize trajectories and flows on interactive maps;
3. clean and preprocess mobility data using state-of-the-art techniques, such as trajectory clustering, compression, segmentation, and filtering;
4. analyze mobility data by using the main measures characterizing mobility patterns both at the individual and at the collective level, such as the computation of travel and characteristic distances, object and location entropies, location frequencies, waiting times, origin-destination matrices, and more;
5. run the most popular mechanistic generative models to simulate individual mobility, such as the Exploration and Preferential Return model (EPR) and its variants (Section 6), and commuting and migratory flows, such as the Gravity
   Model and the Radiation Model;
6. estimate the privacy risk associated with the analysis of a given mobility dataset through the simulation of the reidentification risk associated with a vast repertoire of privacy attacks.

• scikit-mobility is publicly available on GitHub at the following link: https://scikit-mobility.github.io/scikit-mobility/.

• the documentation describing all the classes and functions of scikit-mobility
  is available at https://scikit-mobility.github.io/scikit-mobility/.

Please cite the scikit-mobility paper (https://arxiv.org/pdf/1907.07062.pdf) if you use the library for your analyses ;-)

Install scikit-mobility on Google Colab

Import the library