{"id":19446488,"url":"https://github.com/dcs-training/datavisualisationwithr","last_synced_at":"2025-04-25T01:32:08.941Z","repository":{"id":134064807,"uuid":"368253588","full_name":"DCS-training/DataVisualisationWithR","owner":"DCS-training","description":"Data Visualisation with R Workshop (delivered by the Centre in December 2020).  This workshop is focusing on visualising your data. 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This is the Readme File for the **Data Visualisation with R** Workshop (delivered by the Centre in December 2020). \n\nThis workshop is focusing on **visualising your data** . \n\nThere is much more you can do with R and R Studio and there are a lot of video tutorials you can watch and posts you can read: \n\n- If you want to learn more on **Data Wrangling** with R: [https://www.linkedin.com/learning/data-wrangling-in-r/welcome?u=50251009 ](https://www.linkedin.com/learning/data-wrangling-in-r/welcome?u=50251009)[https://datacarpentry.org/R-ecology-lesson/03-dplyr.html ](https://datacarpentry.org/R-ecology-lesson/03-dplyr.html)\n- If you want to keep learn **small bits over a long period** of time this is a very interesting approach[ https://www.linkedin.com/learning/r-for-data-science- lunchbreak-lessons/exercise-files?u=50251009 ](https://www.linkedin.com/learning/r-for-data-science-lunchbreak-lessons/exercise-files?u=50251009)\n- **Machine Learning** with R[ https://machinelearningmastery.com/machine- learning-in-r-step-by-step/ ](https://machinelearningmastery.com/machine-learning-in-r-step-by-step/)[https://www.datacamp.com/community/tutorials/machine-learning-in-r ](https://www.datacamp.com/community/tutorials/machine-learning-in-r)\n- If you want to learn more on using **R and GIS together**  \n[http://research.shca.ed.ac.uk/past-by-numbers/ ](http://research.shca.ed.ac.uk/past-by-numbers/)[https://www.jessesadler.com/post/gis-with-r-intro/ ](https://www.jessesadler.com/post/gis-with-r-intro/)\n \n\nMore generally, the good thing of R being an Open Source software means you can find  a lot of help online. If at any point of your research you get stuck on something just google the issue and 99% of times someone else posted about it already! \n\nThe best sites on where to **find info and help** are: \n\n- [https://stackoverflow.com/ ](https://stackoverflow.com/)\n- [https://www.r-bloggers.com/ ](https://www.r-bloggers.com/)\n\nFinally if you want to **learn more about what R can do** you can find more info in here: \n\n- [https://www.r-project.org/about.html ](https://www.r-project.org/about.html)\n- [https://blog.revolutionanalytics.com/2012/07/a-big-list-of-the-things-r-can-do.html ](https://blog.revolutionanalytics.com/2012/07/a-big-list-of-the-things-r-can-do.html)\n- [https://simplystatistics.org/2019/03/13/10-things-r-can-do-that-might-surprise- you/ ](https://simplystatistics.org/2019/03/13/10-things-r-can-do-that-might-surprise-you/)\n\nWhat you are going to find in this repo\n\n- In  the  ***installation  instructions***  you  can  find  the  installation instructions.  \n- In the ***DataVisCode***  you can find all the R Script. \n- In the ***datasets*** you are going to find all information concerning the datasets used. \n- In the ***RVisualisation.pptx*** you are going to find the ppt presentation used during the workshop \n\n\nHow to set an R project  \n\n- We are going to cover the subject during the first class but you can find more info on how to set a project in here[ https://support.rstudio.com/hc/en- us/articles/200526207-Using-Projects ](https://support.rstudio.com/hc/en-us/articles/200526207-Using-Projects)\n- Or you can watch this video:[ https://www.youtube.com/watch?v=pyJMWlDptYw ](https://www.youtube.com/watch?v=pyJMWlDptYw)\n- For this class you would need 3 subfolders : \n- Data \n- Code  \n- Graphs\n\n\n## Software Installation\n\nBelow are the steps to do so and get set. \n\n## On Noteable\n\n1. Go to https://noteable.edina.ac.uk/login\n2. Login with your EASE credentials\n3. Select RStudio as a personal notebook server and press start\n4. Go to File \u003eNew Project\u003eVersion Control\u003eGit\n5. Copy and Paste this repository URL https://github.com/DCS-training/PCA-2023 as the Repository URL\n6. The Project directory name will filled in automatically but you can change it if you want your folder in Notable to have a different name\n7. Decide where to locate the folder. By default, it will locate it in your home directory \n8. Press Create Project\n\nCongratulations you have now pulled the content of the repository on your Notable server space the last thing you need to do is to install the packages not already installed in Noteable.\n\n1. Open the 'Install.R' file and run the code within it \n2. Now you can open the 'PCA.R' file and you can follow along\n\n## On your own machine\n\n### R and RStudio\n\n* R and RStudio are separate downloads and installations. R is the\nunderlying statistical computing environment, but using R alone is no\nfun. RStudio is a graphical integrated development environment (IDE) that makes\nusing R much easier and more interactive. You need to install R before you\ninstall RStudio. After installing both programs, you will need to install \nsome specific R packages within RStudio. Follow the instructions below for\nyour operating system, and then follow the instructions to install\n**`tidyverse`** and **`RSQLite`**.\n\n#### Windows\n\n\u003e ## If you already have R and RStudio installed\n\u003e\n\u003e * Open RStudio, and click on \"Help\" \u003e \"Check for updates\". If a new version is\n\u003e available, quit RStudio, and download the latest version for RStudio.\n\u003e * To check which version of R you are using, start RStudio and the first thing\n\u003e  that appears in the console indicates the version of R you are\n\u003e  running. Alternatively, you can type `sessionInfo()`, which will also display\n\u003e  which version of R you are running. Go on\n\u003e  the [CRAN website](https://cran.r-project.org/bin/windows/base/) and check\n\u003e whether a more recent version is available. If so, please download and install\n\u003e it. You can [check here](https://cran.r-project.org/bin/windows/base/rw-FAQ.html#How-do-I-UNinstall-R_003f) for\n\u003e more information on how to remove old versions from your system if you wish to do so.\n{: .solution}\n\n\u003e ## If you don't have R and RStudio installed\n\u003e\n\u003e * Download R from\n\u003e  the [CRAN website](https://cran.r-project.org/bin/windows/base/release.htm).\n\u003e * Run the `.exe` file that was just downloaded\n\u003e * Go to the [RStudio download page](https://www.rstudio.com/products/rstudio/download/#download)\n\u003e * Under *Installers* select **RStudio x.yy.zzz - Windows Vista/7/8/10** (where x, y, and z represent version numbers)\n\u003e * Double click the file to install it\n\u003e * Once it's installed, open RStudio to make sure it works and you don't get any\n\u003e error messages.\n{: .solution}\n\n\n#### macOS\n\n\u003e ## If you already have R and RStudio installed\n\u003e\n\u003e * Open RStudio, and click on \"Help\" \u003e \"Check for updates\". If a new version is\n\u003e\tavailable, quit RStudio, and download the latest version for RStudio.\n\u003e\t* To check the version of R you are using, start RStudio and the first thing\n\u003e\t  that appears on the terminal indicates the version of R you are running. Alternatively, you can type `sessionInfo()`, which will \n\u003e\talso display which version of R you are running. Go on\n\u003e\t  the [CRAN website](https://cran.r-project.org/bin/macosx/) and check\n\u003e\t  whether a more recent version is available. If so, please download and install\n\u003e\t  it.\n{: .solution}\n\n\u003e ## If you don't have R and RStudio installed\n\u003e\n\u003e * Download R from\n\u003e   the [CRAN website](https://cran.r-project.org/bin/macosx/).\n\u003e * Select the `.pkg` file for the latest R version\n\u003e * Double click on the downloaded file to install R\n\u003e * It is also a good idea to install [XQuartz](https://www.xquartz.org/) (needed\n\u003e   by some packages)\n\u003e * Go to the [RStudio download page](https://www.rstudio.com/products/rstudio/download/#download)\n\u003e * Under *Installers* select **RStudio x.yy.zzz - Mac OS X 10.6+ (64-bit)**\n\u003e   (where x, y, and z represent version numbers)\n\u003e * Double click the file to install RStudio\n\u003e * Once it's installed, open RStudio to make sure it works and you don't get any\n\u003e   error messages.\n{: .solution}\n\n#### Linux\n\n* Follow the instructions for your distribution\n from [CRAN](https://cloud.r-project.org/bin/linux), they provide information\n to get the most recent version of R for common distributions. For most\n distributions, you could use your package manager (e.g., for Debian/Ubuntu run\n `sudo apt-get install r-base`, and for Fedora `sudo yum install R`), but we\n don't recommend this approach as the versions provided by this are\n usually out of date. In any case, make sure you have at least R 3.5.1.\n* Go to the [RStudio download\n  page](https://www.rstudio.com/products/rstudio/download/#download)\n* Under *Installers* select the version that matches your distribution, and\n   install it with your preferred method (e.g., with Debian/Ubuntu `sudo dpkg -i\n   rstudio-x.yy.zzz-amd64.deb` at the terminal).\n* Once it's installed, open RStudio to make sure it works and you don't get any\n   error messages.\n\n### Organizing your working directory\n\nUsing a consistent folder structure across your projects will help keep things\norganized, and will help you to find/file things in the future. This\ncan be especially helpful when you have multiple projects. In general, you may\ncreate directories (folders) for **scripts**, **data**, and **documents**. \nIf you want to learn more about how to get set have a look (https://datacarpentry.org/R-ecology-lesson/00-before-we-start.html)[https://datacarpentry.org/R-ecology-lesson/00-before-we-start.html]\n\n\nAll material here collected is free to use but it is covered by a [![License: CC BY-NC 4.0](https://licensebuttons.net/l/by-nc/4.0/80x15.png)](https://creativecommons.org/licenses/by-nc/4.0/) license\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdcs-training%2Fdatavisualisationwithr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdcs-training%2Fdatavisualisationwithr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdcs-training%2Fdatavisualisationwithr/lists"}