DataVisualisationWithR

Hello Everyone! This is the Readme File for the Data Visualisation with R Workshop (delivered by the Centre in December 2020).

This workshop is focusing on visualising your data .

There 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:

• If you want to learn more on Data Wrangling with R: https://www.linkedin.com/learning/data-wrangling-in-r/welcome?u=50251009 https://datacarpentry.org/R-ecology-lesson/03-dplyr.html
• 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
• Machine Learning with R https://machinelearningmastery.com/machine- learning-in-r-step-by-step/ https://www.datacamp.com/community/tutorials/machine-learning-in-r
• If you want to learn more on using R and GIS together
  http://research.shca.ed.ac.uk/past-by-numbers/ https://www.jessesadler.com/post/gis-with-r-intro/

More 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!

The best sites on where to find info and help are:

• https://stackoverflow.com/
• https://www.r-bloggers.com/

Finally if you want to learn more about what R can do you can find more info in here:

• https://www.r-project.org/about.html
• https://blog.revolutionanalytics.com/2012/07/a-big-list-of-the-things-r-can-do.html
• https://simplystatistics.org/2019/03/13/10-things-r-can-do-that-might-surprise- you/

What you are going to find in this repo

• In the installation instructions you can find the installation instructions.
• In the DataVisCode you can find all the R Script.
• In the datasets you are going to find all information concerning the datasets used.
• In the RVisualisation.pptx you are going to find the ppt presentation used during the workshop

How to set an R project

• 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
• Or you can watch this video: https://www.youtube.com/watch?v=pyJMWlDptYw
• For this class you would need 3 subfolders :
• Data
• Code
• Graphs

Software Installation

Below are the steps to do so and get set.

On Noteable

1. Go to https://noteable.edina.ac.uk/login
2. Login with your EASE credentials
3. Select RStudio as a personal notebook server and press start
4. Go to File >New Project>Version Control>Git
5. Copy and Paste this repository URL https://github.com/DCS-training/PCA-2023 as the Repository URL
6. 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
7. Decide where to locate the folder. By default, it will locate it in your home directory
8. Press Create Project

Congratulations 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.

1. Open the 'Install.R' file and run the code within it
2. Now you can open the 'PCA.R' file and you can follow along

On your own machine

R and RStudio

• R and RStudio are separate downloads and installations. R is the underlying statistical computing environment, but using R alone is no fun. RStudio is a graphical integrated development environment (IDE) that makes using R much easier and more interactive. You need to install R before you install RStudio. After installing both programs, you will need to install some specific R packages within RStudio. Follow the instructions below for your operating system, and then follow the instructions to install tidyverse and RSQLite.

Windows

If you already have R and RStudio installed

• Open RStudio, and click on "Help" > "Check for updates". If a new version is available, quit RStudio, and download the latest version for RStudio.
• To check which version of R you are using, start RStudio and the first thing that appears in the console indicates the version of R you are running. Alternatively, you can type sessionInfo(), which will also display which version of R you are running. Go on the CRAN website and check whether a more recent version is available. If so, please download and install it. You can check here for more information on how to remove old versions from your system if you wish to do so. {: .solution}

If you don't have R and RStudio installed

• Download R from the CRAN website.
• Run the .exe file that was just downloaded
• Go to the RStudio download page
• Under Installers select RStudio x.yy.zzz - Windows Vista/7/8/10 (where x, y, and z represent version numbers)
• Double click the file to install it
• Once it's installed, open RStudio to make sure it works and you don't get any error messages. {: .solution}

macOS

If you already have R and RStudio installed

• Open RStudio, and click on "Help" > "Check for updates". If a new version is available, quit RStudio, and download the latest version for RStudio.
  • To check the version of R you are using, start RStudio and the first thing that appears on the terminal indicates the version of R you are running. Alternatively, you can type sessionInfo(), which will also display which version of R you are running. Go on the CRAN website and check whether a more recent version is available. If so, please download and install it. {: .solution}

If you don't have R and RStudio installed

• Download R from the CRAN website.
• Select the .pkg file for the latest R version
• Double click on the downloaded file to install R
• It is also a good idea to install XQuartz (needed by some packages)
• Go to the RStudio download page
• Under Installers select RStudio x.yy.zzz - Mac OS X 10.6+ (64-bit) (where x, y, and z represent version numbers)
• Double click the file to install RStudio
• Once it's installed, open RStudio to make sure it works and you don't get any error messages. {: .solution}

Linux

• Follow the instructions for your distribution from CRAN, they provide information to get the most recent version of R for common distributions. For most distributions, you could use your package manager (e.g., for Debian/Ubuntu run sudo apt-get install r-base, and for Fedora sudo yum install R), but we don't recommend this approach as the versions provided by this are usually out of date. In any case, make sure you have at least R 3.5.1.
• Go to the RStudio download page
• Under Installers select the version that matches your distribution, and install it with your preferred method (e.g., with Debian/Ubuntu sudo dpkg -i rstudio-x.yy.zzz-amd64.deb at the terminal).
• Once it's installed, open RStudio to make sure it works and you don't get any error messages.

Organizing your working directory

Using a consistent folder structure across your projects will help keep things organized, and will help you to find/file things in the future. This can be especially helpful when you have multiple projects. In general, you may create directories (folders) for scripts, data, and documents. If 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]

All material here collected is free to use but it is covered by a license