How to develop a project on R studio?

Summary

This article includes information on RStudio. What purpose does RStudio serve? The notable differences between R and RStudio along with the sequential procedure to develop a project on RStudio are also discussed in this write-up.

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1. Data Analytics using R

What does RStudio do?

A majority of people have the tendency to organize their notes in a haphazard fashion. Scientific Projects usually start with random note-making processes, moving on to some code development, then a manuscript is made, all of which eventually gets jumbled-up together. There are a lot of obvious reasons to convince you to not go for this type of “data mismanagement”:

• You will have a really hard time differentiating between original and modified data. 
• It gets really cumbersome because it mixes files and the various extensions together.
• It is very likely to take you a lot of time in order to actually search for things, and then relate accurate figures to the exact code that has been used to create it.

Being able to give you a project in an organized layout will make your life a lot easier. It will not only help you ensure the integrity of your data but you will able to share your code with your class-mate or collaborator in an easier way. A well-managed data also enables you to easily upload your code along with presenting the manuscript. What’s more? It becomes simple to get back on the project after a break.

Luckily, in this tech-savvy world, a lot many tools and packages are available to help you manage and organize your data, project reports and work effectively. One of these tools is RStudio. The RStudio IDE is developed by RStudio, Inc. which is a commercial enterprise founded by JJ Allaire who is the creator of the programming language ColdFusion.

“RStudio is an integrated development environment (IDE) for R Language. It comprises of a console, syntax-highlighting editor which assists in executing the code directly, along with tools for plotting, debugging, and data workspace management.” RStudio is available both in commercial and open source editions which is supported by various Operating Systems like Windows, Mac, and Linux. It runs either on the desktop or in a browser connected to RStudio Server or RStudio Server Pro like Debian/Ubuntu, Red Hat/CentOS, and SUSE Linux.

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There are amazing features associated with RStudio. These include:

1. You can access RStudio locally.
2. It highlights the syntax, completes the coding and, provides smart indentation. So, when you hit the tab-key, RStudio will try to autocomplete the code for you. This definitely saves a lot of time and typo errors, if any.
3. You can execute R coding straight from the source editor.
4. You can quickly jump to function definitions.
5. It simplifies the management of multiple working directories by using projects.
6. It provides integrated R help and documentation. Using RStudio along with knitr allows you to seamlessly document what you are doing at the same instant. It also provides a smooth-running way of saving figures and output. Instead of writing code in a normal text file, you write it in a simple markdown
7. It also includes an interactive debugger to identify and rectify errors within the span of a few seconds.
8. It has extensive package development tools.

RStudio has the feature of Windows docking, i.e., all the relevant windows that you want at the moment, are docked together. The source file containing your code is located in the upper left and those commands appear when you run them in the R interpreter which is there on the bottom left.  Plots and help files appear in the bottom right. The upper right area shows your graphical workspace. Basically, it is all docked together in a single application window.

Now, in the Graphical Workspace, type 1 s () in the interpreter and you will get the following output: [ 1] “df “. But apart from this, there is a list of objects in your workspace which is there in the upper right panel of the window and by just clicking on a name, voila! it appears on the screen with a graphical view of that object.

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Difference between R and R Studio

In a nutshell, R is a programming language or a software environment used for scientific computing and graphics while RStudio is an IDE for using R and develop R Programming scripts. While R is the language using which you can perform statistical calculations, RStudio gives you the required platform to develop Programmes and run coding on R.

• You can use R without RStudio like on Rcmdr, JRG, Tinn-R, and Eclipse but you can’t use RStudio without R, so R is a pre-requisite.
• RStudio unifies with R as an IDE to provide further functionality. RStudio puts together a source code editor, build automation tools and a debugger.

How to develop a project on R Studio?

RStudio is definitely the best IDE available because of its user-friendly and open-source structure. It is a part of the Anaconda platform.

You need to follow three basic steps in the same sequence in order to run R and RStudio on your system.

• Install R
• Then, install RStudio
• Lastly, install R Packages

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In order to create a new project in RStudio

• Click on the “File” menu button and then on “New Project”.
• Click on “New Directory”.
• Click on “New Project”.
• Type in the name of the directory to store your project, e.g. “my_firstproject”.
• If available, select the checkbox for “Create a git repository.”
• Click on the “Create Project” button.

If you want to know more about developing a project on R Studio, you can check our course on Data Analytics using R.

In this course, you will learn the basics of data analysis & perform real-time analysis on world happiness and diamond quality datasets. You will also learn to perform visualization and manipulation of data using R. And, you will learn about the usage of various packages like ggplot2 and dplyr in R.

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How to develop a project on R studio?