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MovingPandas: Presubmission Inquiry #14

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2 of 9 tasks
anitagraser opened this issue Nov 9, 2019 · 3 comments
Closed
2 of 9 tasks

MovingPandas: Presubmission Inquiry #14

anitagraser opened this issue Nov 9, 2019 · 3 comments

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@anitagraser
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Submitting Author: Anita Graser (@anitagraser)
Package Name: movingpandas
One-Line Description of Package: Implementation of Trajectory classes and functions built on top of GeoPandas
Repository Link (if existing): https://github.com/anitagraser/movingpandas


Description

  • Include a brief paragraph describing what your package does:

MovingPandas is a package for dealing with movement data. MovingPandas implements a Trajectory class and corresponding methods based on GeoPandas. A trajectory has a time-ordered series of point geometries. These points and associated attributes are stored in a GeoDataFrame. MovingPandas implements spatial and temporal data access and analysis functions (covered in the open access publication [0]) as well as plotting functions.

[0] Graser, A. (2019). MovingPandas: Efficient Structures for Movement Data in Python. GI_Forum ‒ Journal of Geographic Information Science 2019, 1-2019, 54-68. doi:10.1553/giscience2019_01_s54. URL: https://www.austriaca.at/rootcollection?arp=0x003aba2b

Scope

  • Please indicate which category or categories this package falls under:

    • Data retrieval
    • Data extraction
    • Data munging
    • Data deposition
    • Data visualization
    • Reproducibility
    • Geospatial
    • Education
    • Unsure/Other (explain below)
  • Explain how the and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

Geospatial (primary): The MovingPandas Trajectory class implements is a spatio-temporal data model for movement data.

Data visualization (secondary): The implemented plot functions enable straight-forward movement data exploration that goes beyond plotting the individual point locations by ensuring that trajectories are represented by linear segments between consecutive points.

  • Who is the target audience and what are scientific applications of this package?

Movement data / trajectories appear in many different scientific domains, including physics, biology, ecology, chemistry, transport and logistics, astrophysics, remote sensing, and more.
For example, the provided tutorials cover the analysis of migrating birds as well as the analysis of ship movement within a port.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?

scikit-mobility (https://github.com/scikit-mobility/scikit-mobility) is a similar package which is also in an early development stage and also deals with movement data. They implement TrajectoryDataFrames and FlowDataFrames on top of Pandas instead of GeoPandas. There is little overlap in the covered use cases and implemented functionality (comparing MovingPandas tutorials and scikit-mobility tutorials). MovingPandas focuses on spatio-temporal data exploration with corresponding functions for data manipulation and analysis. scikit-mobility on the other hand focuses on computing human mobility metrics, generating synthetic trajectories and assessing privacy risks.

  • Any other questions or issues we should be aware of?:

None

P.S. Have feedback/comments about our review process? Leave a comment here

@lwasser
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lwasser commented Nov 11, 2019

hey @anitagraser !! thank you for this submission. we will have a look at it and will get back to you. Welcome to pyopensci!!

@lwasser
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lwasser commented Nov 14, 2019

hi @anitagraser !! we discussed moving pandas today and would like for you to submit it to pyopensci! the next steps, please open a new submission issue for the tool - and i will respond to you there!! Thank you for this inquiry!!

@anitagraser
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Will do, thanks @lwasser !

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