![]() ![]() ![]() All of the R scripts will now be contained within the RStudio project and saved in the project folder.Installing R and Contributed Packages Contributed Packages Now that you have an RStudio project set up you can start creating R scripts (or R markdown documents) or whatever you need to complete you project. The downside to this is that you will need to rerun your R code every time you open you project. You don’t have to do this (many people don’t) but we prefer to start with a completely clean workspace whenever we open our projects to avoid any potential conflicts with things we have done in previous sessions. This ensures that every time you open your project you start with a clean R session. RData into workspace at startup’ and ‘Save workspace to. Click on the ‘General’ tab on the left hand side and then change the values for ‘Restore. The last thing we suggest you do is select Tools -> Project Options. You can check this out in the ‘Files’ tab in RStudio (or in Finder if you’re on a Mac or File Explorer in Windows). Rproj file contains various project options (but you shouldn’t really interact with it) and can also be used as a shortcut for opening the project directly from the file system (just double click on it). Once your new project has been created you will now have a new folder on your computer that contains an RStudio project file called first_project.Rproj. Finally, hit the ‘Create Project’ to create the new project. We always tick the ‘Open in new session’ box as well. If you want to change the location of the directory on your computer click the ‘Browse…’ button and navigate to where you would like to create the directory. Now enter the name of the directory you want to create in the ‘Directory name:’ field (we’ll call it first_project for this Chapter). You can also create a new project by clicking on the ‘Project’ button in the top right of RStudio and selecting ‘New Project…’ In this Chapter we will create a project in a new directory. You can create either an entirely new project, a project from an existing directory or a version controlled project (see the GitHub Chapter for further details about this). To create a project, open RStudio and select File -> New Project. See this video for step-by-step instructions on how to create and work with RStudio projects This means that you can have multiple instances of RStudio open at the same time (if that’s your thing) or you can very easily switch between projects without fear of them interfering with each other. The nice thing about RStudio Projects is that each project has its own directory, workspace, history and source documents so different analyses that you are working on are kept completely separate from each other. An RStudio Project keeps all of your R scripts, R markdown documents, R functions and data together in one place. There are also a few simple steps you can take right at the start of any project to help keep things shipshape.Ī great way of keeping things organised is to use RStudio Projects. ![]() Thankfully, there are some nice features in R and RStudio that make it quite easy to manage a project. Lastly, having a well organised project reduces the risk of introducing bugs or errors into your workflow and if they do occur (which inevitably they will at some point), it makes it easier to track down these errors and deal with them efficiently. This is even more relevant nowadays as it’s never been easier to collect vast amounts of data which can be saved across 1000’s or even 100,000’s of separate data files. ![]() In addition, it’s much easier to write code to automate tasks when files are well organised and are sensibly named. A well documented project that has a consistent and logical structure increases the likelihood that you can pick up where you left off with minimal fuss no matter how much time has passed. There’s nothing more frustrating than coming back to a project months (sometimes years) later and have to spend days (or weeks) figuring out where everything is, what you did and why you did it. Clear project organisation makes it easier for both you (especially the future you) and your collaborators to make sense of what you’ve done. 1.4.2 Integrated developement environementsĪs with most things in life, when it comes to dealing with data and data analysis things are so much simpler if you’re organised. ![]()
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