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We’ve used gitbook to keep all the material we’ve written about R on the RStudio Documentation up to date, and add a new chapter on importing data into R.

We’ve added a new live editing feature to RStudio Manipulate. Just choose the equation you want to edit, then click on the three horizontal lines (the three horizontal dashes) above the example or equation to start editing. (Note: the “three horizontal dashes” should display above the example or equation before you start editing, but for some users this does not happen on all versions of RStudio etc. but you should see the three dashes after you click on the equation. It just takes a moment for the dashes to load.)

Now that we have our first file created, let’s take a closer look at the options available in the R-Studio interface. Remember that while this book has been written to make it easy to get started, many of the more advanced RStudio features are hidden. You will have to dig around for them.

library(rstudioapi)

When this opens, go to the Workbench panel, which is the horizontal bar at the top of the editor:

library(rstudioapi)

Next, go to the R console by clicking R (1) in the Workbench panel.

The R-Studio team has made a lot of improvements to RStudio in this release. But it would be hard to tackle everything, so I’ve listed a number of the most obvious ones:

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RStudio also allows you to integrate your current, full-featured R environment with your work and play world. It lets you view and run R code from the same environment you use to develop web applications. The version you are using is currently 1.0.5, but expect RStudio to grow and develop with each new version of R.

The next time you are in R, and you need to start coding, perhaps instead of opening an editor, you use R Studio. If you need help, stop by rstudio.org.

RStudio 1.2 is now available! The product has been updated to version 1.2, and it will be distributed in the next 1-2 days. Full notes on the 1.2 release, and the reasons why it is recommended for all users can be found here on the RStudio website.

For most users, updating to 1.2 will be automatic. If you aren’t ready, there are two ways to force an update. First, log into the RStudio website and click on the Update button. RStudio will automatically check for and install the update.

The second way is to use the rstudio-installer package available on CRAN. This is a Python script that will install RStudio on any platform. It provides these options:

However, please note that updating RStudio on Ubuntu requires you to use the apt-get command to perform the update. If you use the GUI or the OS installer, then it’s possible your system may break when the update is performed. At that time, it will be necessary to either start a new session or restart the machine to make sure it’s completely updated.

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When you install R-Studio for the first time, you are asked to create a user name and password. This is important because the operations that you perform with RStudio (such as creating projects, opening files, and compiling code) require that you have a license number that can be assigned to that user. Additionally, when you connect RStudio to a remote database and you want the remote server to see that you have a valid license number, you also need to provide a license number for that user. As such, this is where you are able to provide your license information. Although the license may be active for a period of time, the license information is permanent.

After your R-Studio license is active, you are able to create projects, access to the R console, and compile R code in RStudio. You can even, if you choose, use RStudio as an IDE for Ruby, PHP, Perl, and Python projects. You can also manage your Git repositories and work with Git scripts, as well as open project files, find files, and start and stop multiple instances of RStudio at once.

There are also several additional features, including the ability to create a shortcut on your Windows desktop so that you can run RStudio with the drag-and-drop method, and the ability to have help pop-up when you hover over a function. The next paragraph describes the features that are available in this release.

You can run Windows programs using RStudio (such as MATLAB, Simulink, MS Excel, Textmaker, Mathematica, Mathematica notebook files, etc), and you can save files in several different formats: R, MS-DOS, MS Windows, and ZIP. Additionally, you can load projects and work with several popular databases (including Access, DB2, MySQL, ODBC, Oracle, PostgreSQL, SQLite, SQL Server, Sybase, Windows, and Xbase). The local drives on your machine are also accessible through RStudio. You can view network drives if you want.

An extremely useful feature of RStudio is that you can perform all of your operations on a single project at once. For example, you can have 30 projects open at once, and you can have 10 of them loaded on the screen at one time.

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The review unit that R-Studio sent to me was a Mountain Lion 64-bit copy that could be used both to recover files on a drive where data was lost and on a clean drive of the same size. That said, R-Studio has a wide range of features that are useful for data recovery and includes support for many storage types and file systems.

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Main benefits of R-Studio

According to the paper, R-Studio is the result of a collection of open source packages, including the R-Presence, RStudio, and the rweb package.

R-Studio is already installed on every Linux distribution. You can sign in to it by typing ‘rstudio’ and your username in the terminal/command prompt. On the rstudio main menu, you can find a few areas like R documentation, a help browser, new project wizard, etc.

R-Studio is designed to have a GUI-style user interface. While it’s very easy to use, it’s a bit limited in the manner in which it allows you to customize your user experience. For example, you can’t easily customize toolbars in the user interface. However, the RStudio is very customizable from within the R console.

The R-Studio free software is an interactive and visual programming environment to perform R analyses and simulations. You can use R-Studio to prepare and run various types of data analyses, explore data, create visualizations, and make presentations to others. In R-Studio, you can also load other packages to extend the functionality available in the free version of R-Studio. Such packages can be accessed in the RStudio, and more extensions can be added.

This attribute can give R a lot of flexibility in terms of understanding your data and letting you examine it. “When you use an editor like RStudio, it gives you the ability to work with things as you create the object, so youll see things inline,” says Liu. You dont have to create objects piecemeal.

RStudio also has the well-known debugger and history-based error-reporting and fixing toolsets, he says. “With the debugger, you can interact directly with the R object.

Who Uses R-Studio and Why Is It Important?

RStudio is a popular and well-established IDE that allows you to run R programs from within the RStudio window. You can, therefore, test your R code interactively in your favorite text editor, and then use the Run button to execute the code. Once your code is ready, you can open the main GUI window of R and run the code there as well.

Sophisticated uses of R include genomic data analysis (the plethora of genome-wide association data), meteorological modeling, and government statistics. With R, people are also using it to solve the next generation of big problems: social media, internet-of-things, molecular simulation, and computing power crunching.

When I first started using R, I tried to get the syntax without using any IDE. Then, Rstudio became very useful for me, so I started using it. Then, when I had to analyze time-series data, I was still using the command line to plot and process the data, so I felt being quite comfortable with EZR. However, I wonder whether being efficient with EZR is a good reason for learning R?

To help you out with the programming process, two things have happened. The first is RStudio. RStudio (formerly RInsight) is a complete development environment for R, including a text editor, plotting tools, debugging tools, shell, and package management. The second is R, which can create, edit, and compile package files.

RStudio has many features to make coding in R easier for anyone. For instance, instead of needing separate packages for data cleaning and plotting, RStudio offers cleaner ways to use these packages. For example, you can run a command (such as ggplot2::ggplot) from RStudio. A third-party package can be added to RStudio to do the data cleaning or plotting.

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R-Studio Features

First things first, the basic features that RStudio gives you are a way to create and manipulate R data frames, run, plot, select, rename and delete them, browse for files and folders on the local hard drive, open and close RStudio sessions, and take notes.

The graphical interface to RStudio lets you start a new R session, create new files and folders, save the current session, open any of the previously saved sessions, and run reports to show tables and graphs. You can also add new text documents to an existing session, open documents from other applications, and easily create new R objects in the workspace. Additional features include saving your work, saving sessions to file, setting session options like prompt lines or notifications, synchronizing the time between multiple computers running the same version of RStudio, searching through projects with regular expressions and case insensitive filters, and watching for changes between two documents on disk or across a network.

RStudio can save any output that you can generate. Its easy to create reports, histograms, scatterplots, bar charts, matrixes, Parzen windows, contour plots, 3D scatter plots, and box plots. Additionally, you can browse and delete individual files, groups, folders, and more.

Besides the files and folders that RStudio manages, you can also browse for objects in the workspace and change their names, filter files and folders based on their content, or run a specific report that you can save to file.

RStudio also enables you to display multiple plots at once. You can change the size of the plot area, lock individual plots, pan and zoom, add multiple annotations to individual plots, and add interactive widgets, such as sliders and buttons, to the plots.

RStudio has very useful graphing tools. It supports multiple series as well as multiple axes per series. Its also easy to add annotations and create custom plots. You can add colored lines, circles, and markers to an individual plot, and modify the positions of the markers and lines.

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What is R-Studio good for?

RStudio is really meant to make analyzing and visualizing data easier by streamlining certain functions within R. RStudio can do for R what the Visual Basic IDE did for Microsoft Visual Basic and Visual C++. This functionality is made possible by the shiny package, which, if youre unfamiliar with R, is a package for R that makes the process of creating web applications fairly simple and easy to learn. There are even tools for creating the website for your shiny app. RStudio has a built-in developer console. If you want, you can run your code in RStudio and see immediate results. If your code is incomplete or even if you want to debug it as youre developing the code, simply click the debug button in the console. This will start a debugging session in the RStudio window. In this way you can step through code without entering into the workspace, or you can simply run all code in one window without starting a debugging session. If you only want to build your package, that is run your shiny app, click the build button in the console. You can also debug your package interactively on your desktop. When you run your shiny app on the web via ShinyAppBuilder, you can debug it as you build it. The Shiny App Builder will ensure it runs with a real web server.

Another of the great things about the RStudio IDE is its file organization and in-editor code navigation features. Clicking the file icon in the toolbar will open the file in the source code editor. You can also search for a symbol in a file by searching for the text it appears in. Simply highlight the text and press the enter key (note, this may need to be done more than once as youre usually looking at a longer list of returned symbols and only highlight the one you are actually looking for).

The last great thing about the RStudio IDE is its editor. The editor can be quite flexible. For example, if you click the color palette button in the toolbar, RStudio will show you the various colors that it can currently use. Pressing the tab key (the green tab key) and then the space key will hide the contents of the line currently displayed in the editor.

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What is R-Studio and what is it for

There are many advantages to using R, one of them being that it is open source,
meaning that programmers can create an interactive environment with whatever features
they like.

RStudio is not just a framework to create R scripts and run them.
RStudio is much more than that.
RStudio provides a full work environment for data science.
When we write our scripts in R we are scripting R.
RStudio extends the basic functionality of R to include a broad array of
data manipulation and data visualization tools.
There are many more useful features than we are able to discuss in a single
article, and we suggest you explore the full set of tools available in the
Package Repositories tab on the left side of the window.

RStudio offers a framework that provides support for the
installation and management of many different programming languages, including
R, Perl, Python, Java, and others.

A key feature of RStudio is that it creates an environment on your machine
that allows you to interface with spreadsheets directly with R.
If the data is not already stored in R, then it can be stored to a
spreadsheet file and then imported to R.
From R, you can run the commands to transform and analyze the data in the
spreadsheet.

The RStudio IDE allows you to build interactive statistical and scientific
workshops on your data using R. You can write code in R, execute
scripts, and simultaneously edit code, and even share your efforts with
others through the use of a central folder that you and your colleagues are
able to work on simultaneously. For a more in-depth explanation of the IDE,
see the next section.

Note that you must have some prior knowledge of R and how to use the
R-commanding language to use RStudio, as well as some familiarity with
the R-commanding language to work in the RStudio environment.

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What is R-Studio?

It is essentially a larger IDE for R. In the same way that an IDE (like an
RStudio) allows you to edit, run, debug, check for lint, and maybe create
python scripts, the RSTUDIO has similar tools that allow you to work with R
and R projects in a more organized fashion.

You sure can. When you click on the Edit
button next to the file that you want to save, RSTUDIO will also open the
editor for that script. You will find that you are not editing the code, but
the script can still be edited using the editor for that language (e.g.,
Python, Java, C++ etc.). You will notice that R will be in the editor’s title bar
which is useful for loading modules, functions, and environments. You can use
the auto complete feature in the
editor and add in new functions and variables, and you can use the command
edit all to do so.

You can install multiple RStudio installations on your Ubuntu system. If you wish to run multiple RStudio instances, you can do so by opening a new terminal and running the command Rstudio > /home/dcuser/.local/bin/Rstudio, which opens a copy of the default RStudio executable. Remember to set up your scripts to work with the new RStudio executable before trying to install BiocParallel on new RStudio instances.