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reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["carpentries","data-carpentry","data-visualisation","data-visualization","data-wrangling","english","geospatial","geospatial-data","lesson","open-educational-resources","r","stable"],"created_at":"2024-08-05T03:01:26.540Z","updated_at":"2026-03-11T07:03:49.718Z","avatar_url":"https://github.com/datacarpentry.png","language":"R","funding_links":["https://github.com/sponsors/carpentries","https://www.zeffy.com/en-US/donation-form/donate-to-make-a-difference-7497"],"categories":["Python"],"sub_categories":[],"readme":"[![DOI](https://zenodo.org/badge/128225991.svg)](https://zenodo.org/badge/latestdoi/128225991)\n[![Website](https://github.com/datacarpentry/r-intro-geospatial/actions/workflows/website.yml/badge.svg)](https://github.com/datacarpentry/r-intro-geospatial/actions/workflows/website.yml)\n[![Create a Slack Account with us](https://img.shields.io/badge/Create_Slack_Account-The_Carpentries-071159.svg)](https://slack-invite.carpentries.org/)\n[![Slack Status](https://img.shields.io/badge/Slack_Channel-dc--geospatial-E01563.svg)](https://carpentries.slack.com/messages/C9ME7G5RD)\n\n# Intro to R for Geospatial data\n\n\u003c!-- TODO: Update first pararaph of the introduction if they data changes --\u003e\n\nAn introduction to R for non-programmers using the [Gapminder][gapminder] data.\nPlease see [https://datacarpentry.org/r-intro-geospatial](https://datacarpentry.org/r-intro-geospatial) for a rendered\nversion of this material,\n[the lesson template documentation][lesson-example]\nfor instructions on formatting, building, and submitting material,\nor run `make` in this directory for a list of helpful commands.\n\nThe goal of this lesson is to revise best practices for using R in data\nanalysis. This lesson is a modification of the [Software Carpentry: Programming with R](https://swcarpentry.github.io/r-novice-gapminder), and is part of the [Data Carpentry Geospatial Curriculum](https://datacarpentry.org/geospatial-workshop/). It introduces the R skills needed in the [Introduction to Raster and Vector Geospatial Data lesson](https://datacarpentry.org/r-raster-vector-geospatial).\n\nR is commonly used in many scientific disciplines for statistical analysis and\nits array of third-party packages. These materials are designed to provide\nattendees with a concise introduction in the fundamentals of R, and to introdue\nbest practices for scientific computing: breaking down analyses into modular\nunits, task automation, and encapsulation, before getting started with working\nwith geospatial data.\n\nNote that this workshop focuses on the fundamentals of the programming\nlanguage R, and not on statistical analysis.\n\nThe lesson contains material than can be taught in about 4 hours. The\n[instructor notes\npage](https://datacarpentry.org/r-intro-geospatial/guide/index.html) has some\nsuggested lesson plans suitable for a one or half day workshop.\n\n#### Maintainers:\n\n- Johanna Bayer\n- Mike Mahoney\n- Alber Sánchez\n- Kristi Liu\n- Cooper Kimball-Rhines\n\n#### Previous maintainers:\n\n- Leah Wasser\n- Jemma Stachelek\n- Tyson Swetnam\n- Lauren O'Brien\n- Janani Selvaraj\n- Lachlan Deer\n- Chris Prener\n- Juan Fung\n\n[gapminder]: https://www.gapminder.org/\n[lesson-example]: https://carpentries.github.io/lesson-example\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatacarpentry%2Fr-intro-geospatial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdatacarpentry%2Fr-intro-geospatial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatacarpentry%2Fr-intro-geospatial/lists"}