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 social media, survey data, etc.); - extract 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 data set
scikit-mobility
Pappalardo L;
2019
Abstract
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 social media, survey data, etc.); - extract 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 data setI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
