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Development","sub_category":"Education","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"![Build and Deploy Website](https://github.com/datacarpentry/R-ecology-lesson/workflows/Build%20and%20Deploy%20Website/badge.svg)\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_Ecology_R-E01563.svg)](https://carpentries.slack.com/messages/C9X9EC405)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3264888.svg)](https://doi.org/10.5281/zenodo.3264888)\n\n# _Data Carpentry: R for data analysis and visualization of Ecological Data_\n\nThis is an introduction to R designed for participants with no programming\nexperience. It can be taught in 3/4 of a day (approximately 6 hours).\nIt is a redesigned version of [the original Data Carpentry lesson](https://doi.org/10.5281/zenodo.12684301). \n\nThe initial effort towards this redesign was done by [Michael Culshaw-Maurer](https://github.com/MCMaurer) in another repository in The Carpentries Incubator: https://github.com/carpentries-incubator/R-ecology-lesson (now archived). See Michael's notes while preparing the redesign in [the update_plans.md file](https://github.com/carpentries-incubator/R-ecology-lesson/blob/main/update_plan.md) of that repository.\n\nThe lesson starts with information about the R programming language and the RStudio interface. It then moves to loading in data and exploring how to visualise it with ggplot2. The next episode takes learners through an exploration of data frames and some common data cleaning operations, before discussing vectors and factors. The final episode introduces the flow of data in R, and how to combine operations to select, filter, and mutate a data frame.\n\nIllustrations from the previous version of this lesson are now available in the\n[carpentries/commons](https://github.com/carpentries/commons/tree/main/illustrations/) repository.\n\n## Providing feedback on this lesson\n\nIf you teach this redesigned lesson, please [open an issue](https://github.com/datacarpentry/R-ecology-lesson/issues/new) on this repository to share your experience. \n\n## Prerequisites\n\nThe lesson assumes no prior knowledge of R or RStudio.\nLearners should have R and RStudio installed on their computers. They will also\nneed to be able to install R packages from CRAN, create directories, and\ndownload files.\nSee [the lesson website](https://datacarpentry.org/R-ecology-lesson/index.html#setup)\nfor instructions on installing R, RStudio, and the required R packages.\n\n## Contributing\n\nContributions to the content and development of these lesson are very welcome!\nIf you would like to contribute, we encourage you to review our [contributing guide](CONTRIBUTING.Rmd).\n\n## Questions\n\nIf you have any questions or feedback, please open an issue, contact the\nmaintainers, or come chat with us on the\n[Slack Channel for this lesson](https://carpentries.slack.com/messages/C9X9EC405).\nIf you don't already have a Slack account with the Carpentries, you can\n[create one](https://slack-invite.carpentries.org/).\n\n## Maintainers\n\n* [Hugo Gruson](https://github.com/Bisaloo)\n* [Carolyn Koehn](https://github.com/CarolynKoehn)\n* [Teofil Nakov](https://github.com/teofiln)\n* [Elizabeth Stregger](https://github.com/estregger)\n\n","funding_links":["https://github.com/sponsors/carpentries","https://www.zeffy.com/en-US/donation-form/donate-to-make-a-difference-7497"],"readme_doi_urls":["https://doi.org/10.5281/zenodo.3264888","https://doi.org/10.5281/zenodo.12684301"],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["carpentries-incubator","beta","tidyverse","spreadsheet","data-management","fair-principles","sustainable-software","tibfds","geospatial-data","carpentries-lab"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/11892","html_url":"https://ost.ecosyste.ms/projects/11892"}