Package: pymove
Use PyMove and go much furtherInformationPackage StatusLicensePython VersionPlatformsBuild StatusPyPi versionPyPi DownloadsConda versionConda DownloadsCode QualityCode CoverageWhat is PyMovePyMove is a Python library for processing and visualization
of trajectories and other spatial-temporal data.We will also release wrappers to some useful Java libraries
frequently used in the mobility domain.Read the full documentation onReadTheDocsMain FeaturesPyMoveproposes:A familiar and similar syntax to Pandas;Clear documentation;Extensibility, since you can implement your main data structure by
manipulating other data structures such as
Dask DataFrame, numpy arrays, etc., in addition to adding new modules;Flexibility, as the user can switch between different data structures;Operations for data preprocessing, pattern mining and data visualization.Creating a Virtual EnvironmentIt is recommended to create a virtual environment to use pymove.Requirements: Anaconda Python distribution installed and accessibleIn the terminal client enter the following whereenv_nameis the name
you want to call your environment, and replacex.xwith the Python version
you wish to use. (To see a list of available python versions first,
type conda search "^python$" and press enter.)conda create -n <env_name> python=x.xPress y to proceed. This will install the Python version and all theassociated anaconda packaged libraries atpath_to_your_anaconda_location/anaconda/envs/env_nameActivate your virtual environment. To activate or switch into your
virtual environment, simply type the following where yourenvname is the
name you gave to your environment at creation.conda activate <env_name>Now install the package from eitherconda,piporgithubCondainstalationconda install -c conda-forge pymovePipinstallationpip install pymoveGithubinstallationClone this repositorygit clone https://github.com/InsightLab/PyMoveSwitch to folder PyMovecd PyMoveSwitch to a new branchgit checkout -b developerMake a pull of branchgit pull origin developerInstall pymove in developer modemake devFor windows usersIf you installed frompiporgithub, you may encounter an error related toshapelydue to some dll dependencies. To fix this, runconda install shapely.ExamplesYou can see examples of how to use PyMovehereMapping PyMove methods with the Paradigms of Trajectory Data MiningZHENG 2015.1:Spatial Trajectories→pymove.coreMoveDataFrameDiscreteMoveDataFrame2:Stay Point Detection→pymove.preprocessing.stay_point_detectioncreate_or_update_move_stop_by_dist_timecreate_or_update_move_and_stop_by_radius3:Map-Matching→pymove-osmnx4:Noise Filtering→pymove.preprocessing.filtersby_bboxby_datetimeby_labelby_idby_tidclean_consecutive_duplicatesclean_gps_jumps_by_distanceclean_gps_nearby_points_by_distancesclean_gps_nearby_points_by_speedclean_gps_speed_max_radiusclean_trajectories_with_few_pointsclean_trajectories_short_and_few_pointsclean_id_by_time_max5:Compression→pymove.preprocessing.compressioncompress_segment_stop_to_point6:Segmentation→pymove.preprocessing.segmentationbbox_splitby_dist_time_speedby_max_distby_max_timeby_max_speed7:Distance Measures→pymove.distancesmedpmedteuclidean_distance_in_metershaversine8:Query Historical Trajectories→pymove.query.queryrange_queryknn_query9:Managing Recent Trajectories10:Privacy Preserving11:Reducing Uncertainty12:Moving Together Patterns13:Clustering→pymove.models.pattern_mining.clusteringelbow_methodgap_statisticsdbscan_clustering14:Freq. Seq. Patterns15:Periodic Patterns16:Trajectory Classification17:Trajectory Outlier / Anomaly Detection→pymove.semantic.semanticoutlierscreate_or_update_out_of_the_bboxcreate_or_update_gps_deactivated_signalcreate_or_update_gps_jumpcreate_or_update_short_trajectorycreate_or_update_gps_block_signalfilter_block_signal_by_repeated_amount_of_pointsfilter_block_signal_by_timefilter_longer_time_to_stop_segment_by_idCiteThe library was originally created during the bachelor's thesis of 2 students from the Federal University of Ceará, so you can cite using both works.@mastersthesis{arina2019,
	title        = {Uma arquitetura e implementação do módulo de pré-processamento para biblioteca PyMove},
	author       = {Arina De Jesus Amador Monteiro Sanches},
	year         = 2019,
	school       = {Universidade Federal Do Ceará},
	type         = {Bachelor's thesis}
}
@mastersthesis{andreza2019,
	title        = {Uma arquitetura e implementação do módulo de visualização para biblioteca PyMove},
	author       = {Andreza Fernandes De Oliveira},
	year         = 2019,
	school       = {Universidade Federal Do Ceará},
	type         = {Bachelor's thesis}
}PublicationsUma arquitetura e implementação do módulo de pré-processamento para biblioteca PyMoveUma arquitetura e implementação do módulo de visualização para biblioteca PyMoveAvaliação de técnicas de aumento de dados para trajetóriasImplementação de algoritmos para análise de similaridade de trajetória na biblioteca PyMoveUseful list of related libraries and linksHandling GPS Data with Pythonmplleaflet - Easily convert matplotlib plots from Python into interactive Leaflet web mapsPykalmanRamer-Douglas-Peucker algorithmKnee point detection in PythonTrajSuite Java LibraryGraphHopper Map-Matching Java Library