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260 results for “movingpandas”

  1. Even more human research:

    Elkin-Frankston et al. (2025). Beyond boundaries: a location-based toolkit for quantifying group dynamics in diverse contexts. Cogn. Research 10, 10 (2025).
    doi.org/10.1186/s41235-025-006

    "We first segmented time periods when the group was in motion by identifying break periods using the stop detection feature from the MovingPandas Python package"

  2. Even more human #MovementBehavior research:

    Elkin-Frankston et al. (2025). Beyond boundaries: a location-based toolkit for quantifying group dynamics in diverse contexts. Cogn. Research 10, 10 (2025).
    doi.org/10.1186/s41235-025-006

    "We first segmented time periods when the group was in motion by identifying break periods using the stop detection feature from the MovingPandas Python package"

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience #HumanMobility

  3. Even more human #MovementBehavior research:

    Elkin-Frankston et al. (2025). Beyond boundaries: a location-based toolkit for quantifying group dynamics in diverse contexts. Cogn. Research 10, 10 (2025).
    doi.org/10.1186/s41235-025-006

    "We first segmented time periods when the group was in motion by identifying break periods using the stop detection feature from the MovingPandas Python package"

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience #HumanMobility

  4. Even more human #MovementBehavior research:

    Elkin-Frankston et al. (2025). Beyond boundaries: a location-based toolkit for quantifying group dynamics in diverse contexts. Cogn. Research 10, 10 (2025).
    doi.org/10.1186/s41235-025-006

    "We first segmented time periods when the group was in motion by identifying break periods using the stop detection feature from the MovingPandas Python package"

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience #HumanMobility

  5. Even more human #MovementBehavior research:

    Elkin-Frankston et al. (2025). Beyond boundaries: a location-based toolkit for quantifying group dynamics in diverse contexts. Cogn. Research 10, 10 (2025).
    doi.org/10.1186/s41235-025-006

    "We first segmented time periods when the group was in motion by identifying break periods using the stop detection feature from the MovingPandas Python package"

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience #HumanMobility

  6. New research using yours truely:

    Koszewski et al. (2025). Utilizing IoT Sensors and Spatial Data Mining for Analysis of Urban Space Actors’ Behavior in University Campus Space Design.
    doi.org/10.3390/s25051393

    "Trajectories were processed by the MovingPandas Python library, which offers several valuable processing algorithms"

    For the full list of publications we're aware of, check out:

    github.com/movingpandas/moving

  7. New #IOT research using yours truely:

    Koszewski et al. (2025). Utilizing IoT Sensors and Spatial Data Mining for Analysis of Urban Space Actors’ Behavior in University Campus Space Design.
    doi.org/10.3390/s25051393

    "Trajectories were processed by the MovingPandas Python library, which offers several valuable processing algorithms"

    For the full list of publications we're aware of, check out:

    github.com/movingpandas/moving

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience

  8. New #IOT research using yours truely:

    Koszewski et al. (2025). Utilizing IoT Sensors and Spatial Data Mining for Analysis of Urban Space Actors’ Behavior in University Campus Space Design.
    doi.org/10.3390/s25051393

    "Trajectories were processed by the MovingPandas Python library, which offers several valuable processing algorithms"

    For the full list of publications we're aware of, check out:

    github.com/movingpandas/moving

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience

  9. New #IOT research using yours truely:

    Koszewski et al. (2025). Utilizing IoT Sensors and Spatial Data Mining for Analysis of Urban Space Actors’ Behavior in University Campus Space Design.
    doi.org/10.3390/s25051393

    "Trajectories were processed by the MovingPandas Python library, which offers several valuable processing algorithms"

    For the full list of publications we're aware of, check out:

    github.com/movingpandas/moving

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience

  10. New #IOT research using yours truely:

    Koszewski et al. (2025). Utilizing IoT Sensors and Spatial Data Mining for Analysis of Urban Space Actors’ Behavior in University Campus Space Design.
    doi.org/10.3390/s25051393

    "Trajectories were processed by the MovingPandas Python library, which offers several valuable processing algorithms"

    For the full list of publications we're aware of, check out:

    github.com/movingpandas/moving

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience

  11. Urban Mobility Insights with & in 

    Today, I want to point out a blog post over at written together with my fellow co-authors and @emeraldseu project team member Argyrios Kyrgiazos.

    For the technically inclined, the highlight are the presented UDFs in Snowflake to process and transform the trajectory data.

    anitagraser.com/2024/12/17/urb

  12. 🎉 We're happy to announce the release of 0.20, now without fiona dependency

    For the full changelog see:
    github.com/movingpandas/moving

    Freshly forged packages 📦  are available now on conda-forge

  13. Pleasure to see more and more use from students:

    "we utilize the stop detection tools provided by MovingPandas"

    Wicaksono, S. B. (2024). From Data Cleaning to Predictive Models: A Strategic Approach to Analyzing Bus and Ship Trajectories. Master Thesis in Data Science, Department of Mathemetics, University of Padova.

    thesis.unipd.it/handle/20.500.

  14. Our tutorials and analysis notebooks now come with plenty of usage examples for the new explore() function which provides powered interactive plots

    You probably already know and appreciate it from and now you can also enjoy it in

    movingpandas.org/examples

  15. 0.19 released!

    This release is the first to support 1.0. Additionally, this release adds multiple new features, including: New explore() function adds interactive / maps New support for trajectory For the full change log, check out the release page.

    anitagraser.com/2024/08/23/mov

  16. And most recently in :

    Van Deursen, J., Creany, N., Smith, B., Freimund, W., Avgar, T., & Monz, C. A. (2024). Recreation specialization: Resource selection functions as a predictive tool for . Applied Geography, 167, 103276. - " and packages in were used to analyze the GPS data collected and calculate the thirteen spatio-temporal metrics"

    sciencedirect.com/science/arti

  17. And most recently in #Geopraphy:

    Van Deursen, J., Creany, N., Smith, B., Freimund, W., Avgar, T., & Monz, C. A. (2024). Recreation specialization: Resource selection functions as a predictive tool for #ProtectedArea #RecreationManagement. Applied Geography, 167, 103276. - "#GeoPandas and #MovingPandas packages in #Python were used to analyze the GPS data collected and calculate the thirteen spatio-temporal metrics"

    sciencedirect.com/science/arti

    #GIScience #GISChat #MobilityAnalytics #MovementData