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spreg

Spatial econometric regression in Python

https://github.com/pysal/spreg

Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 1 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ✓
    Committers with academic emails
    3 of 21 committers (14.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (8.9%) to scientific vocabulary

Keywords

econometrics geography spatial-analysis spatial-regression spatial-statistics statistics

Keywords from Contributors

spatial-data topology pysal spatial-network network-analysis graph-theory regionalization routing geoparquet transportation
Last synced: 6 months ago · JSON representation

Repository

Spatial econometric regression in Python

Basic Info
  • Host: GitHub
  • Owner: pysal
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage: https://pysal.org/spreg/
  • Size: 8.23 MB
Statistics
  • Stars: 81
  • Watchers: 22
  • Forks: 26
  • Open Issues: 15
  • Releases: 26
Topics
econometrics geography spatial-analysis spatial-regression spatial-statistics statistics
Created almost 8 years ago · Last pushed 7 months ago
Metadata Files
Readme License

README.md

spreg

unittests codecov PyPI - Python Version PyPI Anaconda-Server Badge GitHub commits since latest release (branch) DOI

PySAL Spatial Econometrics Package

spreg, short for “spatial regression,” is a Python package to estimate simultaneous autoregressive spatial regression models. These models are useful when modeling processes where observations interact with one another. This package is part of a refactoring of PySAL.

License information

See the file "LICENSE.txt" for information on the history of this software, terms & conditions for usage, and a DISCLAIMER OF ALL WARRANTIES.

Owner

  • Name: Python Spatial Analysis Library
  • Login: pysal
  • Kind: organization

GitHub Events

Total
  • Create event: 7
  • Release event: 4
  • Issues event: 5
  • Watch event: 12
  • Delete event: 1
  • Issue comment event: 20
  • Push event: 21
  • Pull request review event: 4
  • Pull request event: 28
  • Fork event: 5
Last Year
  • Create event: 7
  • Release event: 4
  • Issues event: 5
  • Watch event: 12
  • Delete event: 1
  • Issue comment event: 20
  • Push event: 21
  • Pull request review event: 4
  • Pull request event: 28
  • Fork event: 5

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 566
  • Total Committers: 21
  • Avg Commits per committer: 26.952
  • Development Distribution Score (DDS): 0.786
Past Year
  • Commits: 30
  • Committers: 6
  • Avg Commits per committer: 5.0
  • Development Distribution Score (DDS): 0.467
Top Committers
Name Email Commits
Pedro Amaral p****a@g****m 121
James Gaboardi j****i@g****m 86
Serge Rey s****y@g****m 75
ljwolf l****f@g****m 50
weikang9009 w****9@g****m 48
Pablo Estrada p****d@e****c 37
ljwolf l****2@a****u 34
Phil Stephens p****s@g****m 28
David Folch d****h@g****m 20
Dani Arribas d****e@g****m 16
Dani Arribas-Bel d****l@g****m 12
dependabot[bot] 4****] 11
Nick Malizia n****a@g****m 10
eli knaap ek@k****m 10
Pedro Amaral p****o@P****l 2
Wei Kang w****g@g****l 1
Jay j****a@a****u 1
Charles Schimdt s****c@g****m 1
Taylor Oshan t****n@g****m 1
Xun Li l****0@g****m 1
Serge Rey s****m 1
Committer Domains (Top 20 + Academic)
asu.edu: 2 knaaptime.com: 1 espol.edu.ec: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 59
  • Total pull requests: 121
  • Average time to close issues: 6 months
  • Average time to close pull requests: 17 days
  • Total issue authors: 23
  • Total pull request authors: 10
  • Average comments per issue: 2.39
  • Average comments per pull request: 1.32
  • Merged pull requests: 101
  • Bot issues: 0
  • Bot pull requests: 24
Past Year
  • Issues: 4
  • Pull requests: 24
  • Average time to close issues: 2 months
  • Average time to close pull requests: 2 days
  • Issue authors: 4
  • Pull request authors: 5
  • Average comments per issue: 1.25
  • Average comments per pull request: 1.54
  • Merged pull requests: 17
  • Bot issues: 0
  • Bot pull requests: 3
View more stats
Top Authors
Issue Authors
  • jGaboardi (25)
  • sjsrey (4)
  • shuai-zhou (3)
  • pedrovma (3)
  • pabloestradac (3)
  • knaaptime (3)
  • tdhoffman (2)
  • gboeing (1)
  • jooglyp (1)
  • eroubenoff (1)
  • dbursy (1)
  • martinfleis (1)
  • JosiahParry (1)
  • darribas (1)
  • rhstanton (1)
Pull Request Authors
  • pedrovma (53)
  • jGaboardi (29)
  • dependabot[bot] (26)
  • knaaptime (8)
  • weikang9009 (6)
  • pabloestradac (5)
  • sjsrey (3)
  • tdhoffman (2)
  • dschult (2)
  • JosiahParry (2)
Top Labels
Issue Labels
maint/admin (10) CI (5) docs (4) bug (3) GSOC2020 (3) GSOC2022 (2) GitHub-Actions (2) tests (1) code formatting (1) question (1) enhancement (1) scipy2018 (1)
Pull Request Labels
github_actions (29) dependencies (28) docs (11) maint/admin (9) CI (9) bug (6) GitHub-Actions (4) GSOC2020 (3) enhancement (3) GSOC2022 (2) release (2) code formatting (1) WIP (1)

Packages

  • Total packages: 3
  • Total downloads:
    • pypi 32,218 last-month
  • Total docker downloads: 218
  • Total dependent packages: 15
    (may contain duplicates)
  • Total dependent repositories: 61
    (may contain duplicates)
  • Total versions: 39
  • Total maintainers: 4
pypi.org: spreg

PySAL Spatial Econometric Regression in Python

  • Versions: 26
  • Dependent Packages: 3
  • Dependent Repositories: 45
  • Downloads: 32,218 Last month
  • Docker Downloads: 218
Rankings
Docker downloads count: 1.8%
Downloads: 2.1%
Dependent repos count: 2.2%
Dependent packages count: 2.4%
Average: 4.3%
Forks count: 8.2%
Stargazers count: 9.3%
Maintainers (4)
knaaptime sjsrey ljwolf pedrovma
Last synced: 6 months ago
conda-forge.org: spreg
  • Versions: 7
  • Dependent Packages: 12
  • Dependent Repositories: 8
Rankings
Dependent packages count: 5.1%
Dependent repos count: 12.2%
Average: 23.6%
Forks count: 36.0%
Stargazers count: 41.0%
Last synced: 6 months ago
anaconda.org: spreg

spreg, short for “spatial regression,” is a Python package to estimate simultaneous autoregressive spatial regression models. These models are useful when modeling processes where observations interact with one another. This package is part of a refactoring of PySAL.

  • Versions: 6
  • Dependent Packages: 0
  • Dependent Repositories: 8
Rankings
Dependent repos count: 39.6%
Average: 46.4%
Forks count: 46.8%
Stargazers count: 48.1%
Dependent packages count: 51.2%
Last synced: 6 months ago

Dependencies

.github/workflows/build_docs.yml actions
  • actions/checkout v3 composite
  • ad-m/github-push-action master composite
  • mamba-org/provision-with-micromamba main composite
.github/workflows/release_and_publish.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • pCYSl5EDgo/cat master composite
  • pypa/gh-action-pypi-publish master composite
  • softprops/action-gh-release v1 composite
.github/workflows/unittests.yml actions
  • actions/checkout v3 composite
  • codecov/codecov-action v3 composite
  • mamba-org/provision-with-micromamba main composite
environment.yml pypi
pyproject.toml pypi
  • libpysal >=4.0.0
  • numpy >=1.3
  • pandas *
  • scikit-learn >=0.22
  • scipy >=0.11