{"id":25697751,"url":"https://github.com/geodacenter/geoda","last_synced_at":"2025-05-15T04:05:00.105Z","repository":{"id":35990607,"uuid":"40282352","full_name":"GeoDaCenter/geoda","owner":"GeoDaCenter","description":"GeoDa: An introduction to spatial data analysis","archived":false,"fork":false,"pushed_at":"2025-05-06T17:48:51.000Z","size":196582,"stargazers_count":744,"open_issues_count":88,"forks_count":156,"subscribers_count":37,"default_branch":"master","last_synced_at":"2025-05-06T18:43:12.384Z","etag":null,"topics":["spatial-data-analysis","spatial-regression"],"latest_commit_sha":null,"homepage":"http://geodacenter.github.io","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/GeoDaCenter.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"COPYING","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2015-08-06T03:29:18.000Z","updated_at":"2025-05-06T13:59:02.000Z","dependencies_parsed_at":"2023-10-12T05:02:15.417Z","dependency_job_id":"9bf75790-4ff7-41dc-b1e1-865f1d390eaa","html_url":"https://github.com/GeoDaCenter/geoda","commit_stats":{"total_commits":2697,"total_committers":11,"mean_commits":245.1818181818182,"dds":0.6421950315164998,"last_synced_commit":"40003fcd8270f389a07698bfebfb1844b1d64ee2"},"previous_names":[],"tags_count":48,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GeoDaCenter%2Fgeoda","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GeoDaCenter%2Fgeoda/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GeoDaCenter%2Fgeoda/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GeoDaCenter%2Fgeoda/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/GeoDaCenter","download_url":"https://codeload.github.com/GeoDaCenter/geoda/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254270641,"owners_count":22042858,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["spatial-data-analysis","spatial-regression"],"created_at":"2025-02-25T02:30:27.245Z","updated_at":"2025-05-15T04:04:55.091Z","avatar_url":"https://github.com/GeoDaCenter.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![Mac OSX builds](https://github.com/geodacenter/geoda/actions/workflows/osx_build.yml/badge.svg)](https://github.com/geodacenter/geoda/actions/workflows/osx_build.yml)\n[![Ubuntu builds](https://github.com/geodacenter/geoda/actions/workflows/ubuntu_build.yml/badge.svg)](https://github.com/geodacenter/geoda/actions/workflows/ubuntu_build.yml)\n[![Windows builds](https://github.com/geodacenter/geoda/actions/workflows/windows_build.yml/badge.svg)](https://github.com/geodacenter/geoda/actions/workflows/windows_build.yml)\n\n# Acknowledgements #\n\nGeoDa TM is built upon several open source libraries and source-code files.\n\nGeoDa is the flagship program of the GeoDa Center, following a long line of software tools developed by Dr. Luc Anselin. It is designed to implement techniques for exploratory spatial data analysis (ESDA) on lattice data (points and polygons). The free program provides a user friendly and graphical interface to methods of descriptive spatial data analysis, such as spatial autocorrelation statistics, as well as basic spatial regression functionality. The latest version contains several new features such as full space-time data support in all views, a new cartogram, a refined map movie, parallel coordinate plot, 3D visualization, conditional plots (and maps) and spatial regression.\n\nSince its initial release in February 2003, GeoDa's user numbers have increased exponentially, as the chart and map of global users above shows. This includes lab users at universities such as Harvard, MIT, and Cornell. The user community and press embraced the program enthusiastically, calling it a \"hugely important analytic tool,\" a \"very fine piece of software,\" an \"exciting development\" and more.\n\n# Build GeoDa #\n\nPlease read the detail instructions under directory BuildTools/\n\n[Windows](BuildTools/windows/readme.md)\n\n[Mac OSX](BuildTools/macosx/readme.md)\n\n[Linux/Ubuntu](BuildTools/ubuntu/readme.md)\n\nNote:  contributions of build scripts under other platforms are welcomed, please follow the structure of building script under BuildTools/.\n\n# Internationalization #\n\nGeoDa Internationalization (I18n) and Localization(L10n) project aims to provide an online tool that GeoDa users could help to translate the GeoDa UI to different languages.\n\nFor crowdsourcing, we use Google Spreadsheet with the public address [here](https://docs.google.com/spreadsheets/d/1iZa4wCIyTDlIRYoW7229YoZWKZ0lmIiOFsCJG3ZVw-s/edit?usp=sharing). Anyone can access this spreadsheet, and edit each translation.\n\n# Contributors: #\n\n* @corochasco\n* Gulrukh Rakhmatullaeva\n\nThanks for your contributions!\n\n# Dependencies #\n\nBelow is a list of some of these that we'd like to acknowledge.\n\n* GDAL Libraries, version 1.10\n\n        License: X/MIT style Open Source license\n        Authors: many\n        Links: http://www.gdal.org/\n    \n* Boost Libraries, version 1.53\n\n        License: Boost Software License - Version 1.0\n        Authors: many\n        Links: http://www.boost.org/\n              http://www.boost.org/LICENSE_1_0.txt\n\n* Boost.Polygon Voronoi Library, Boost version 1.53\n\n        License: Boost Software License - Version 1.0\n        Author: Andrii Sydorchuk\n        Links: http://www.boost.org/\n              http://www.boost.org/LICENSE_1_0.txt\n\n* wxWidgets Cross-Platform GUI Library, version 2.9.4\n\n        License: The wxWindows Library Licence\n        Authors: Julian Smart, Robert Roebling, and others\n        Links: http://www.wxwidgets.org/\n                http://www.opensource.org/licenses/wxwindows.php\n\n* CLAPACK Linear Algebra Libraries, version 3.2.1\n\n        Authors: many\n        License: Custom by University of Tennessee\n        Links: http://www.netlib.org/clapack/\n                http://www.netlib.org/lapack/lapack-3.2/LICENSE\n\n* Approximate Nearest Neighbor Library, version 0.1\n\n        Note: Full source of 0.1 release included in kNN directory\n        Authors: Sunil Arya and David Mount\n        License: See kNN/AHH.h in included source files\n        Links: http://www.cs.umd.edu/~mount/ANN/\n\n* FastArea.c++ source code\n\n        Note: We have based the source for functions findArea and\n        ComputeArea2D in our file GenGeomAlgs.h from FastArea.c++\n        in Journal of Graphics Tools, 7(2):9-13, 2002\n        Author: Daniel Sunday\n        License: unknown\n        Links: http://www.tandfonline.com/doi/abs/10.1080/10867651.2002.10487556\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgeodacenter%2Fgeoda","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgeodacenter%2Fgeoda","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgeodacenter%2Fgeoda/lists"}