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Releases: d-wasserman/arc-sampling-and-scoring

arc-sampling-and-scoring v2.2

16 Oct 05:52
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Pre-release

A set of ArcGIS tools that assist with sampling and scoring spatial data by enabling proportional allocations, density sampling, and different scoring methods. The documentation for each tool in the scripts folder and toolbox will be placed in the read me in the section below.

Changes from Last Release:

  • Add min-max scaling tool .

  • Reorganize toolbox to use nested toolsets for better organization.

arc-sampling-and-scoring v2.1

14 Oct 03:02
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A set of ArcGIS tools that assist with sampling and scoring spatial data by enabling proportional allocations, density sampling, and different scoring methods. The documentation for each tool in the scripts folder and toolbox will be placed in the read me in the section below.

Changes from Last Release:

  • Percentile Scoring can now just rank tools.
  • Density to vector extents and fillna values changed to reflect more ArcGIS Pro oriented behavior.

arc-sampling-and-scoring v 2.0

11 Nov 07:05
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A set of ArcGIS tools that assist with sampling and scoring spatial data by enabling proportional allocations, density sampling, and different scoring methods. The documentation for each tool in the scripts folder and toolbox will be placed in the read me in the section below.
In this release:

  • ArcTime Tools were moved to a new repository.
  • Project, tbx, and other scripts were remade.
  • Sample graphic for proportional allocation as means of explanation added.

arc-numerical-tools-v1.1.0

30 May 23:33
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A set of ArcGIS tools that use Numpy and Pandas to help with different data analysis tasks such as standardizing data, associating densities to networks, and manipulating spatial-temporal data.
This release:

  • Updates error handling across GP tools to throw Arc compliant error messages.
  • Updates percentile ranking functions to expose more assumptions, support relative ranking within groups, and other edits.

arc-numerical-tools-v1.0.0

29 May 19:04
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A set of ArcGIS tools that use Numpy and Pandas to help with different data analysis tasks such as standardizing data, associating densities to networks, and manipulating spatial-temporal data. These tools are largely short cut utilities, some where parallels at high license levels in the ArcGIS Platforms.