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| "title": "Coding for research in R", | ||
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| "text": "Overview\nThese sessions provide an introduction to coding in R. The aim is to get you comfortable with coding techniques commonly used in scientific research.", | ||
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| "text": "Learning Objectives\n\n\n\n\nGet familiar with the R programming language\nLearn to visualise data\nBe able to manipulate and transform data\n\n\n\n\nTarget audience\nThis course is aimed at people without any prior programming experience. It does however, allow people with some experience to further enhance their knowledge through different level exercises.\n\n\nPrerequisites\nNo prerequisites.\n\n\n\nExercises\nExercises in these materials are labelled according to their level of difficulty:\n\n\n\n\n\n\n\nLevel\nDescription\n\n\n\n\n \nExercises in level 1 are simpler and designed to get you familiar with the concepts and syntax covered in the course.\n\n\n \nExercises in level 2 combine different concepts together and apply it to a given task.\n\n\n \nExercises in level 3 require going beyond the concepts and syntax introduced to solve new problems.", | ||
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| "text": "Citation & authors\nPlease cite these materials if:\n\nYou adapted or used any of them in your own teaching.\nThese materials were useful for your research work. For example, you can cite us in the methods section of your paper: “We carried our analyses based on the recommendations in YourReferenceHere”.\n\n\nYou can cite these materials as:\n\nTavares, H., van Rongen, M., Cardona, A. (2024). Course Development Guidelines. https://cambiotraining.github.io/found-coding-for-research-r/\n\nOr in BibTeX format:\n@misc{YourReferenceHere,\n author = {Tavares, Hugo and van Rongen, Martin and Cardona, Alexia},\n month = {10},\n title = {Course Development Guidelines},\n url = {https://cambiotraining.github.io/found-coding-for-research-r/},\n year = {2024}\n}\nAbout the authors:\nHugo Tavares \nAffiliation: Cambridge Centre for Research Informatics Training Roles: writing - original draft; conceptualisation; software\n\nMartin van Rongen \nAffiliation: Cambridge Centre for Research Informatics Training Roles: writing - review & editing; conceptualisation; software\n\nAlexia Cardona \nAffiliation: Cambridge Centre for Research Informatics Training Roles: conceptualisation", | ||
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| "section": "Acknowledgements", | ||
| "text": "Acknowledgements\n\nThese materials are based on the original course contents of the “Data Carpentry lesson in Ecology”.\nMichonneau F, Teal T, Fournier A, Seok B, Obeng A, Pawlik AN, Conrado AC, Woo K, Lijnzaad P, Hart T, White EP, Marwick B, Bolker B, Jordan KL, Ashander J, Dashnow H, Hertweck K, Cuesta SM, Becker EA, Guillou S, Shiklomanov A, Klinges D, Odom GJ, Jean M, Mislan KAS, Johnson K, Jahn N, Mannheimer S, Pederson S, Pletzer A, Fouilloux A, Switzer C, Bahlai C, Li D, Kerchner D, Rodriguez-Sanchez F, Rajeg GPW, Ye H, Tavares H, Leinweber K, Peck K, Lepore ML, Hancock S, Sandmann T, Hodges T, Tirok K, Jean M, Bailey A, von Hardenberg A, Theobold A, Wright A, Basu A, Johnson C, Voter C, Hulshof C, Bouquin D, Quinn D, Vanichkina D, Wilson E, Strauss E, Bledsoe E, Gan E, Fishman D, Boehm F, Daskalova G, Tavares H, Kaupp J, Dunic J, Keane J, Stachelek J, Herr JR, Millar J, Lotterhos K, Cranston K, Direk K, Tylén K, Chatzidimitriou K, Deer L, Tarkowski L, Chiapello M, Burle M, Ankenbrand M, Czapanskiy M, Moreno M, Culshaw-Maurer M, Koontz M, Weisner M, Johnston M, Carchedi N, Burge OR, Harrison P, Humburg P, Pauloo R, Peek R, Elahi R, Cortijo S, sfn_brt, Umashankar S, Goswami S, Sumedh, Yanco S, Webster T, Reiter T, Pearse W, Li Y (2019). “datacarpentry/R-ecology-lesson: Data Carpentry: Data Analysis and Visualization in R for Ecologists, June 2019.” doi: 10.5281/zenodo.3264888, “http://datacarpentry.org/R-ecology-lesson/”.", | ||
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| "title": "Data & Setup", | ||
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| "text": "Data\nThe data used in these materials is provided as a zip file. Download and unzip the folder to your Desktop to follow along with the materials.\nDownload", | ||
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| "text": "Software\n\nQuarto\nTo develop and render the course materials website, you will need to install Quarto:\n\nDownload and install Quarto (available for all major OS).\nIf you are developing materials using executable .qmd documents, it is recommended that you also install the extensions for your favourite IDE (e.g. RStudio, VS Code).\nIf you are developing materials using JupyterLab or Jupyter Notebooks, please install Jupytext.\n\nUse the paired notebook feature to have synchronised .ipynb/.qmd files. Only .qmd files should be pushed to the repository (.ipynb files have been added to .gitignore).", | ||
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| "text": "3.1 Context\nWhy are we using a programming language? Link in with other courses (reproducible research, stats, visualisation etc)", | ||
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| "text": "3.2 Working directory\n\nLO: understand why we use working directories\nLO: setting up an R project", | ||
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| "text": "3.3 Working with R\n\n3.3.1 Scripts versus console\n\n\n3.3.2 Comments in code\n\n\n3.3.3 Code headings\nLO: Using # heading ---- syntax to organise your code\n\n\n3.3.4 Running code\nLO: running code (simple calculations)\n\n\n3.3.5 Functions and their arguments\nLO: functions & arguments\n\n\n3.3.6 Adding functionality using packages\nLO: adding functionality (installing + loading packages)", | ||
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| "text": "3.4 Summary\n\n\n\n\n\n\nKey points", | ||
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| "text": "4.1 Context\nWe’ve seen examples where we entered data directly into a function. Most of the time we have data from elsewhere, such as a spreadsheet. We’ll build up from a single object; vector; tabular data; brief mention of others (matrices, arrays - linking to day 3)", | ||
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| "section": "4.2 Objects", | ||
| "text": "4.2 Objects\n\n4.2.1 Creating objects\nLO: create objects\n\n\n4.2.2 Using objects\nLO: using objects (calculations etc)\n\n\n4.2.3 Vectors\nLO: create vectors LO: operations with vectors LO: subsetting (indices, conditionals with TRUE/FALSE)\n\n\n4.2.4 Dealing with missing data\nLO: why is missing data important? LO: good practices of dealing with missing data", | ||
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