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R-Studio For Windows

07.11.2021

R-Studio For Windows

RStudio, being much more than a simple IDE, provides several features such as the tight integration knitr, RMarkdown and Shiny that promote. Installer-less versions of RStudio are also available. Name, Size, Published, MD5. RStudio-1.1.463.exe, 85.8 MB, Oct 25 2018 04:58. RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as.

R-Studio For Windows -

RStudio — PC Install and More

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This page is based on the installation of RStudio on a PC computer using the Firefox web browser. The process took place on August 17, 2015. The standard version of RStudio at that time was 0.99.467. Please understand that web pages change, software changes, and installation systems change. Thus, what is recorded here, although true at the moment of recording, may have changed by the time you read this.

Also, as I hope is obvious, the images below have been annotated, in , to show you where you need to point and click.

Just a few quick notes:

  1. We will short-circuit the installation by starting not at the RStudio main web page but rather right at the point where we choose the file to use.
  2. The installation of the software is done in Figure 11.
  3. Following the installation there are sections of this page showing three different ways to start the software. A fourth method, and the one that you will most likely use most often, appears starting in Figure 37.
  4. Starting in Figure 27 we do one quick use of RStudio. This gives us a chance to examine some of the components of the IDE (Integrated Development Environment).
  5. Many of the Figures have been shrunk to facilitate display and printing. This should not compromise the readability of the images; the images are really just there to verify and explain what you should be seeing on your screen.
  6. This material has not been formatted for printing so if you do print it you will get a lot of blank space and the Figure numbers may be separated from the images by page breaks.

To install RStudio, we will go to the RStudio web site at the https://www.rstudio.com/products/rstudio/download2/#download web site. This should open a page almost identical to the one shown in Figure 1. For a PC we want to use the option, the one highlighted by the green box in Figure 1.

Figure 1

The particular installation of Firefox used here was set to ask the user where downloaded files should be saved. The version that you use may or may not be similarly configured. That will not matter since we will use a different feature of Firefox, in Figure 4, to run the downloaded file no matter where it has been saved. [A similar feature exists an any of the other modern browsers.] Firefox first asks if we want to , as shown in Figure 2. We do want to save the file so we click the button.

Figure 2

As just noted, the version of Firefox here wants to have us determine where to save the file. In the case shown here it will be saved in the directory structure although the particular place is immaterial to this presentation. If you see a window such as that shown in Figure 3, just click on the button.

Figure 3

Once the file is downloaded to your computer we need to run the file. On the top bar of the Firefox screen we find the down arrow, , icon as highlighted in Figure 4.

Figure 4

When you click on that icon, a new window shows up displaying the recent downloads. In Figure 5 we see the file that we just downloaded. To run that file we click on the file name as indicated in Figure 5.

Figure 5

At this point, on this computer using Windows 10, the operating system wants to get a confirmation that it is OK to actually run the program that we downloaded. [Note that running a downloaded program is possibly dangerous if the original site had a corrupted or infected file waiting for you.] In this case we are confident that the source of our file is to be trusted so we click the button.

Figure 6

The install program starts. We will just step through the options. Figure 7 shows the first screen and we move on by clicking the button.

Figure 7

The same is true for the window shown in Figure 8.

Figure 8

The same is true for the window shown in Figure 9. However, it is worth noting that the installation program, in Figure 9, is asking about the location of the program's shortcut. By not making any changes here we instruct the installation program to put that shortcut into the menu. We will see this in Figure 26 .

Figure 9

Figure 10 catches the install progress screen as the installation continues.

Figure 10

Finally, in Figure 11, the installation is complete and we can click the button to move forward.

Figure 11

Now that RStudio has been installed, we want to be able to run it. The presentation from here through Figure 26 demonstrates three different ways to start RStudio, either directly from the menu or from an icon that you can put onto your desktop. These are interesting but not essential for this course. The suggested method for this course starts after Figure 37. The presentation from Figure 27 through Figure 36 just walks us through a short problem, allowing us to point out different features of the RStudio environment.

Back in Figure 9 we had the installation program place the shortcut for RStudio onto the menu. If we open that menu either by clicking the Windows icon, , at the extreme lower left of the screen or by typing the Windows key on the bottom left of the keyboard, we will get a new window. Part of that window on my computer is shown in Figure 12 (after scrolling down to display the desired shortcut, ).

To start RStudio just click on that shortcut, as shown in Figure 12.

Figure 12

RStudio opens as shown in Figure 13. The RStudio window is divided into 3 panes, the Console, the Environment (which can alternatively display the History), and the Files (which has a number of other options).

Figure 13

We will come back to this in Figure 27. Before we do that, however, we will look at two ways to put the shortcut icon onto the desktop.

The most straightforward way is to return to the menu, find the shortcut for RStudio, then click and hold on that shortcut and drag it to the desktop where we release the mouse button. This is shown in Figure 14.

Figure 14

Once the shortcut icon is on the desktop we can just double click it to start RStudio.

A much more tedious method to create the shortcut is to start at any open spot on the desktop and right-click the mouse. This opens a small window, one option on which is . Put the cursor on that option and, shortly, a secondary window opens, as shown in Figure 15. Point to the option in that window and click there.

Figure 15

We could type in the location of the file but we will take the slightly longer if somewhat safer approach of looking for it. To that end click on the button.

Figure 16

We want to look on , so click on that.

Figure 17

We want to look on the drive, so click on that.

Figure 18

Next we want to look in but that is not shown in Figure 19.

Figure 19

Therefore, scroll down to find , as shown in Figure 19a. Once we have found it, then click on that item.

Figure 19a

Now we want to find , but again it is not yet visible in Figure 20.

Figure 20

Therefore, scroll down to display as shown in Figure 20a, and then click on that item.

Figure 20a

Now click on the item.

Figure 21

In this window we want to find the option. It is not shown in Figure 22.

Figure 22

Therefore we scroll down to find it, and click on it as shown in Figure 23. At that point we click on the button.

Figure 23

This takes us back to the window that we saw back in Figure 16 but now the location field is filled in, and it is filled correctly. All we need to do now is to click the button.

Figure 24

This brings up our final screen where we click on the button.

Figure 25

The result is a new shortcut, shown in Figure 26, on the desktop.

Figure 26

Once we have the desktop shortcut, we just need to double click on it to start RStudio. We have done so in order to get the RStudio window shown in Figure 27 (which is the same as the one we saw in Figure 13.

Figure 27

As long as we have started RStudio we might as well try it out. We have the following problem. Walking around near the parking lot I found and collected 8 stones. I then weighed those stones and obtained the following measurements.
Weight of the stones I found
4.76.95.25.74.85.36.45.1
We want to put those values into RStudio. To do this, in the Console pane, we enter the command

in the Console after the > prompt.. This produces the image shown in Figure 28.

Figure 28

Now, to have R perform the command, we hit the key on the keyboard. The result is shown in Figure 29.

Figure 29

Our command has caused R to create a variable called , and to assign that variable the list of values that we specified. The Environment pane monitors the variables that have been defined. It also displays the first values stored in those variables. We only have the one variable so far, but we can see it, the fact that it is num meaning numeric, that it has eight values in it (items 1 through 8), and the value of the first few of those items.

Let us do two more operations on the data. First we will ask R to find the mean (the average of the values, i.e., add up the values and divide by the number of values), and second, we will get a summary of the values. The first command is

which we enter and then press the key. R responds with the value 5.5125. The second command is

which produces six values: the lowest value in the data, the 1st quartile, the median value, the mean value, the 3rd quartile, and the largest value in the data. You might note that R gives these with only 3 decimal places whereas R gave the mean value with 4 decimal places.

Figure 30

A completely different kind of command is shown in Figure 31. That command is a function that retrieves the working directory that R and RStudio are using at that time.

Figure 31

The result of using the command is , indicating that as the location of any files that we are using or that we might want to save. More on that later.

We can demonstrate yet another type of command, namely,

shown in Figure 32. The result of that command is a new plot, shown in the lower right pane, that is a bar plot of the data held in the variable .

Figure 32

Finally, we use the command to tell R and RStudio to quit. For Figure 33 we have typed the command and pressed the key. R then asks us if it should save the "workspace". This is also shown in Figure 33.

Figure 33

We want to save the workspace, so we answer "y" and press the key. After that our RStudio session is closed.

[Figure 34 is omitted.]

By "saving the workspace" we have told R to save all of our variables in a "hidden" file called , and to save that file in the "working directory". We can see this if we open RStudio again (by double clicking on the RStudio icon on the desktop). We have done this to generate Figure 35.

Figure 35

Two things to note in Figure 35 are the new last line of the "splash" screen from R telling us that the workspace has been loaded from the file and the fact that the one variable we had in our previous session is still defined.

In fact, if we click on the tab in the lower right pane we change the display to that shown in Figure 36. In that pane we can see that the file is now in that directory, that the file size is 2.6KB, and that it was created on Aug. 17 at 9:24 PM. In fact, a new history file called was created at that same time, the moment when we closed our previous session.

Figure 36

We will finish this introduction with a few more commands shown in Figure 37 along with the resulting output from R. First, the command causes R to display the contents of the variable . Then the command

has R compute the mean and then store that value in the new variable . Note that R does not display the value of xbar at that time, although RStudio displays it in the Environment pane. Then the command causes R to display the value stored in the variable. Finally, the command causes R to ask if it should save the workspace. Again we respond with . Once we press the key the program will save the workspace and close.

Figure 37

At this point we will shift gears and look at the preferred, and expected, method of opening a new RStudio session. To do this we will plug in the USB thumb drive given out in class. When I did this on my computer the response was to open the File Explorer to display the contents of the USB drive. This is shown in Figure 37a.

Figure 37a

Although it is nice to see the contents of the USB drive, at this point we will not be making reference to the existing files. Therefore, at this time we can close the File Explorer by clicking on the X in the upper right corner of the window.

Our approach will be to create a text file that contains just the command and then to save that file in a subdirectory of the USB drive that we will create. Then, we can return to the File Explorer, navigate to that subdirectory, and start a new RStudio session by double clicking on the name of our new file.

We could do this in any number of different text editors but because it is available on any Windows system, we will use Notepad. To find and start Notepad we can just type into the "Ask me anything" box at the lower left of the screen. The result should be something similar to what is shown in Figure 38.

Figure 38

Click on the icon and the program should start with a screen similar to that shown in Figure 39.

Figure 39

Now type the one text line, namely, and press the key to move to a new line. This should show up as in Figure 40.

Figure 40

Then, from the menu bar choose the option and from the new window click on the option, as appears in Figure 41.

Figure 41

This will open a window similar to that shown in Figure 42. In the left pane of Figure 42 we want to find the entry for the USB thumb drive that we just installed.

Figure 42

On this computer we could not see that entry so we needed to scroll down that left pane. Figure 43 now displays that drive as . We click on that entry producing the display given as Figure 43.

Figure 43

None of the files that we saw back in Figure 37a appear here because this window, the one shown in Figure 43, is looking for all of the "Text" files, the ones with the extension. There are none of those files on the USB drive.

However, our task is not to find a file, but to save one in a new folder. To that end we click on the button.

Figure 44

This creates a new folder and it suggests the name for that directory. We, however, will call this folder and we do that by typing that name into the given box as shown in Figure 45.

Figure 45

Once the folder has been created, we still need to navigate to it. We can do this by double clicking on the folder icon to the left of the name. This should bring us to the image in Figure 46. Note, in the location bar near the top of Figure 46, that we are in the proper subdirectory.

Figure 46

Now that we are there we can enter the name of our new file, I have called it and please note that it is important to have the file extension be in this case. We conclude the process of saving the file by clicking on the button.

Figure 47

That leaves us in Notepad. To exit the program we click on the option in the menu and then click on the option in the small window that opens.

Figure 48

Recall that the next step is to find our newly created folder and the file in it via the File Explorer. To do that we start the File explorer by clicking on the folder option at the bottom of the screen, as is shown in Figure 48a.

Figure 48a

Then we can navigate to by clicking on that item in the left pane, and to the drive shown on the window.

Figure 49

All of that should change the display to something like that shown in Figure 50. Once there we can open the folder by clicking on the entry.

Figure 50

This should take us to Figure 51. There we can see the file that we just created. We will double click on that filename, .

Figure 51

This being the first time we have tried this, the computer asks for help in determining which program should be used to open files that have a extension. It does this via a pop-up window like the one shown in Figure 52.

We want to use RStudio so we will make sure it is highlighted (we may need to click on it to do that).

Figure 52

After the RStudio option is highlighted we should be sure that the checkbox for is marked, as it is in Figure 53. Then we can click on the button.

Figure 53

That starts RStudio. This time the RStudio screen is split into 4 panes. The new pane is an editor, built into RStudio, that has not only opened, but it has opened with our file in it.

Having a file into which we can type commands and then, as we will see, execute those commands is a significant advantage. Among other things, it allows us to take our work to another computer, to share our work with others, and to record and publish our work. This is an essential skill that all statisticians need to have.

Figure 54

To demonstrate this, in the editor pane, type the following commands

getwd() stones <- c(4.7, 6.9, 5.2, 5.7, 4.8, 5.3, 6.4, 5.1) girth <- c(10.5,15.3,11.6,12.7,10.7,11.8,14.2,11.4) plot(girth,stones) Actually, if you have this page open and you have your RStudio session open as shown in Figure 54, you can just highlight the commands above, copy them via the key sequence, click on the editor pane, and paste the commands via the key sequence. This saves a lot of typing. Your editor pane should appear as in Figure 55.

Figure 55

Now, to demonstrate executing commands that are in the editor, highlight the command, as shown in Figure 56. Then click on the icon, , on the editor toolbar, indicated in Figure 56.

Figure 56

The result appears in Figure 57. The command has been copied to the Console and performed. It is interesting to note that the working directory for this session is our newly created folder. This is just what we want. When we save the workspace later the files and will be saved in this directory. In that way we are keeping all of our work related to our current problem in one folder.

Figure 57

Returning to the editor, we can highlight our next two commands as shown in Figure 58. Then, we can again click on the icon, , on the editor toolbar to copy those commands to the Console and execute them.

Figure 58

The result is shown in Figure 59.

Figure 59

In Figure 59 we not only see that the commands have been performed, but the two new variables appear in the Environment pane.

To get to Figure 60 we need to highlight our last command in the editor pane and then use the icon to cause the command to be copied and executed.

Figure 60

In Figure 60 we can see the plot created by our simple command.

By creating the plot we have automatically switched the lower right corner pane to the tab. We can click on the tab in that pane to change the display to be more like that shown in Figure 61.

Figure 61

You may notice, in Figure 61, that we still have but one file in our folder.

We return to the editor pane and click on the icon to force saving the changes we have made in the file in the editor. This is shown in Figure 62.

Figure 62

Once that is done we can turn our attention back to the pane where we see that the file is now bigger, 136 bytes vs. the earlier 9 bytes, and the time stamp has been updated.

Figure 63

We can return to the Console where we issue the command and then say that we do want to save the workspace, all shown in Figure 64.

Figure 64

Once we conclude that with the key, RStudio closes.

Returning our attention to the File Explorer, shown in Figure 65, we can see the two new files.

Figure 65

If we double click on our file again, RStudio starts anew. Figure 66 shows this new session. Note that the splash screen shows that the workspace was loaded from our folder, that the file has been loaded into the editor, and that the two variables that we defined are available as shown in the Environment pane. In addition, we can see the three files in the pane.

Figure 66

As usual, we use the command to quit RStudio.

Figure 67

All that remains now is to remove our USB drive. It is a good idea to make sure that the computer thinks it is ok to do this. If the icon is present at the lower right of your screen then click on it. If it is not present, then you may have to click on the up-arrow, shown in the red circle in Figure 68, to find the icon.

Figure 68

This should open a window listing the various devices that can be removed. Such a list appears in Figure 69. Click on the desired item.

Figure 69

The response should be the small window shown in Figure 70. At that point it is safe to remove the USB drive.

Figure 70


Return to Software Installation

©Roger M. Palay     Saline, MI 48176     August, 2015

Источник: https://courses.wccnet.edu/~palay/math160r/rstudiopc.htm

David Zelený

Download the latest version from RStudio website; you will need Desktop version, Open Source Edition for your system; you may click here to get directly to the selection of actual RStudion version. Follow instructions for installation. If you already have RStudio installed in your computer, please check whether you have the latest version and update if you don't (in RStudio menu, go to Help > Check for Updates).

RStudio is a convenient software, which combines R program with text editor and graphical user interface (and offers much more, like organization of scripts and outputs into a projects within single folder, and for advanced users also convenient building of packages, document markup etc.). One thing I found a bit not handy is RStudio's native graphical output - it offers its own unique sizeable graphical output into one of the subpanels (usually the bottom-right one), but it sometimes produces troubles (especially in case when you draw more complex figures). The workaround is to open the original R drawing panel - just type into the console, and new active window will open (you can move it around the screen, or right-click on it by mouse and select “Stay on top” to keep it as the top window always visible on your screen).

Optionally, there is a number of other text editors, which can be associated with R, e.g. Tinn-R. You are free to use the editor of your choice. In the class, I will use RStudio.

Источник: https://davidzeleny.net/wiki/doku.php/recol:install_r

Installing R and RStudio

To get started with R, you need to acquire your own copy. This appendix will show you how to download R as well as RStudio, a software application that makes R easier to use. You’ll go from downloading R to opening your first R session.

Both R and RStudio are free and easy to download.

How to Download and Install R

R is maintained by an international team of developers who make the language available through the web page of The Comprehensive R Archive Network. The top of the web page provides three links for downloading R. Follow the link that describes your operating system: Windows, Mac, or Linux.

Windows

To install R on Windows, click the “Download R for Windows” link. Then click the “base” link. Next, click the first link at the top of the new page. This link should say something like “Download R 3.0.3 for Windows,” except the 3.0.3 will be replaced by the most current version of R. The link downloads an installer program, which installs the most up-to-date version of R for Windows. Run this program and step through the installation wizard that appears. The wizard will install R into your program files folders and place a shortcut in your Start menu. Note that you’ll need to have all of the appropriate administration privileges to install new software on your machine.

Mac

To install R on a Mac, click the “Download R for Mac” link. Next, click on the package link (or the package link for the most current release of R). An installer will download to guide you through the installation process, which is very easy. The installer lets you customize your installation, but the defaults will be suitable for most users. I’ve never found a reason to change them. If your computer requires a password before installing new progams, you’ll need it here.

Binaries Versus Source

R can be installed from precompiled binaries or built from source on any operating system. For Windows and Mac machines, installing R from binaries is extremely easy. The binary comes preloaded in its own installer. Although you can build R from source on these platforms, the process is much more complicated and won’t provide much benefit for most users. For Linux systems, the opposite is true. Precompiled binaries can be found for some systems, but it is much more common to build R from source files when installing on Linux. The download pages on CRAN’s websiteprovide information about building R from source for the Windows, Mac, and Linux platforms.

Linux

R comes preinstalled on many Linux systems, but you’ll want the newest version of R if yours is out of date. The CRAN website provides files to build R from source on Debian, Redhat, SUSE, and Ubuntu systems under the link “Download R for Linux.” Click the link and then follow the directory trail to the version of Linux you wish to install on. The exact installation procedure will vary depending on the Linux system you use. CRAN guides the process by grouping each set of source files with documentation or README files that explain how to install on your system.

32-bit Versus 64-bit

R comes in both 32-bit and 64-bit versions. Which should you use? In most cases, it won’t matter. Both versions use 32-bit integers, which means they compute numbers to the same numerical precision. The difference occurs in the way each version manages memory. 64-bit R uses 64-bit memory pointers, and 32-bit R uses 32-bit memory pointers. This means 64-bit R has a larger memory space to use (and search through).

As a rule of thumb, 32-bit builds of R are faster than 64-bit builds, though not always. On the other hand, 64-bit builds can handle larger files and data sets with fewer memory management problems. In either version, the maximum allowable vector size tops out at around 2 billion elements. If your operating system doesn’t support 64-bit programs, or your RAM is less than 4 GB, 32-bit R is for you. The Windows and Mac installers will automatically install both versions if your system supports 64-bit R.

Using R

R isn’t a program that you can open and start using, like Microsoft Word or Internet Explorer. Instead, R is a computer language, like C, C++, or UNIX. You use R by writing commands in the R language and asking your computer to interpret them. In the old days, people ran R code in a UNIX terminal window—as if they were hackers in a movie from the 1980s. Now almost everyone uses R with an application called RStudio, and I recommend that you do, too.

R and UNIX

You can still run R in a UNIX or BASH window by typing the command:

which opens an R interpreter. You can then do your work and close the interpreter by running when you are finished.

RStudio

RStudio is an application like Microsoft Word—except that instead of helping you write in English, RStudio helps you write in R. I use RStudio throughout the book because it makes using R much easier. Also, the RStudio interface looks the same for Windows, Mac OS, and Linux. That will help me match the book to your personal experience.

You can download RStudio for free. Just click the “Download RStudio” button and follow the simple instructions that follow. Once you’ve installed RStudio, you can open it like any other program on your computer—usually by clicking an icon on your desktop.

The R GUIs

Windows and Mac users usually do not program from a terminal window, so the Windows and Mac downloads for R come with a simple program that opens a terminal-like window for you to run R code in. This is what opens when you click the R icon on your Windows or Mac computer. These programs do a little more than the basic terminal window, but not much. You may hear people refer to them as the Windows or Mac R GUIs.

When you open RStudio, a window appears with three panes in it, as in Figure A.1. The largest pane is a console window. This is where you’ll run your R code and see results. The console window is exactly what you’d see if you ran R from a UNIX console or the Windows or Mac GUIs. Everything else you see is unique to RStudio. Hidden in the other panes are a text editor, a graphics window, a debugger, a file manager, and much more. You’ll learn about these panes as they become useful throughout the course of this book.

The RStudio IDE for R.

Figure A.1: The RStudio IDE for R.

Do I still need to download R?

Even if you use RStudio, you’ll still need to download R to your computer. RStudio helps you use the version of R that lives on your computer, but it doesn’t come with a version of R on its own.

Opening R

Now that you have both R and RStudio on your computer, you can begin using R by opening the RStudio program. Open RStudio just as you would any program, by clicking on its icon or by typing “RStudio” at the Windows Run prompt.

Источник: https://rstudio-education.github.io/hopr/starting.html

RStudio

OverviewAccess the RStudio IDE from anywhere via a web browserMove computation close to the dataScale compute and RAM centrallyPowerful coding tools to enhance your productivityEasily publish apps and reportsPython DevelopmentView Python data, publish and knit in Python and share objects with RAuthor and edit Python code with Jupyter Notebooks, JupyterLab and VSCodeEasily publish and share Jupyter NotebooksProject SharingShare projects & edit code files simultaneously with othersMultiple R VersionsRun multiple versions of R side-by-sideDefine environments for a particular R versionMultiple R and Python SessionsRun multiple analyses in parallelLoad BalancingLoad balance R sessions across two or more serversEnsure high availability using multiple mastersAdministrative DashboardMonitor active sessions and their CPU and memory utilizationSuspend, forcibly terminate, or assume control of any active sessionReview historical usage and server logsEnhanced SecurityLDAP, Active Directory, Google Accounts and system accountsFull support for Pluggable Authentication Modules, Kerberos via PAM, and custom authentication via proxied HTTP headerEncrypt traffic using SSL and restrict client IP addressesAuditing and MonitoringMonitor server resources (CPU, memory, etc.) on both a per-user and system-wide basisSend metrics to external systems with the Graphite/Carbon plaintext protocolHealth check with configurable output (custom XML, JSON)Audit all R console activity by writing input and output to a central locationAdvanced R Session ManagementTailor the version of R, reserve CPU, prioritize scheduling and limit resources by User and GroupProvision accounts and mount home directories dynamically via the PAM Session APIAutomatically execute per-user profile scripts for database and cluster connectivityData ConnectivityRStudio Professional Drivers are ODBC data connectors that help you connect to some of the most popular databasesLauncherStart processes within various systems such as container orchestration platformsSubmit standalone ad hoc jobs to your compute cluster(s) to run computationally expensive R or Python scriptsTutorial APIAutomate interactions with the RStudio IDERemote SessionsConnect to RStudio Workbench directly from RStudio Desktop Pro for more powerful computing resources, freeing up your local system
Источник: https://www.rstudio.com/products/rstudio/

Installing R and RStudio - Easy R Programming

In our previous article, we described what is R and why you should learn R. In this article, we’ll describe briefly how to install R and RStudio on Windows, MAC OSX and Linux platforms. RStudio is an integrated development environment for R that makes using R easier. It includes a console, code editor and tools for plotting.

To make things simple, we recommend to install first R and then RStudio.


Install R for windows

  1. Download the latest version of R, for Windows, from CRAN at : https://cran.r-project.org/bin/windows/base/

Download R for Windows

  1. Double-click on the file you just downloaded to install R

  2. Cick ok –> Next –> Next –> Next …. (no need to change default installation parameters)

Install RStudio on Windows

Download RStudio for Windows

It is relatively simple to install R, but if you need further help you can try the following resources:

This analysis has been performed using R software (ver. 3.2.3).


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Источник: http://www.sthda.com/english/wiki/installing-r-and-rstudio-easy-r-programming
R-Studio
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R-Linux
R-Linux is a free software for Windows OS and Debian/Ubuntu/Fedora/Redhat Linux platforms. This provides basic data recovery and undelete tools that can be used to recover data lost due to damaged, deleted or re-formatted partitions, virus attacks, power failures and system crashes. For a professional data recovery utility, consider R-Studio for Linux
  • R-Tools Technology Inc. is the leading provider of powerful data recovery, undelete, drive image, data security and PC privacy utilities. Our mission is to give our customers around the world the system tools to bring about a visible and substantial increase in viability, production, and ease of use at the lowest possible cost to the customer.
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watch the thematic video

R - Install R and R Studio on Windows 10

David Zelený

Download the latest version from RStudio website; you will need Desktop version, Open Source Edition for your system; you may click here to get directly to the selection of actual RStudion version. Follow instructions for installation. If you already have RStudio installed in your computer, please check whether you have the latest version and update if you don't (in RStudio menu, go to Help > Check for Updates).

RStudio is a convenient software, which combines R program with text editor and graphical user interface (and offers much more, like organization of scripts and outputs into a projects within single folder, and for advanced users also convenient building of packages, document markup etc.). One thing I found a bit not handy is RStudio's native graphical output - it offers its own unique sizeable graphical output into one of the subpanels (usually the bottom-right one), but it sometimes produces troubles (especially in case when you draw more complex figures). The workaround is to open the original R drawing panel - just type into the console, and new active window will open (you can move it around the screen, or right-click on it by mouse and select “Stay on top” to keep it as the top window always visible on your screen).

Optionally, there is a number of other text editors, which can be associated with R, e.g. Tinn-R. You are free to use the editor of your choice. In the class, I will use RStudio.

Источник: https://davidzeleny.net/wiki/doku.php/recol:install_r

Installing R and RStudio

To get started with R, you need to acquire your own copy. This appendix will show you how to download R as well as RStudio, a software application that makes R easier to use. You’ll go from downloading R to opening your first R session.

Both R and RStudio are free and easy to download.

How to Download and Install R

R is maintained by an international team of developers who make the language available through the web page of The Comprehensive R Archive Network. The top of the web page provides three links for downloading R. Follow the link that describes your operating system: Windows, Mac, or Linux.

Windows

To install R on Windows, click the “Download R for Windows” link. Then click the “base” link. Next, click the first link at the top of the new page. This link should say something like “Download R 3.0.3 for Windows,” except the 3.0.3 will be replaced by the most current version of R. The link downloads an installer program, which installs R-Studio For Windows most up-to-date version of R for Windows. Run this program and step through the installation wizard that appears. The wizard will install R into your program files folders and place a shortcut in your Start menu. Note that you’ll need to have all of the appropriate administration privileges to install new software on your machine.

Mac

To install R on a Mac, click the “Download R for Mac” link. Next, click on the package link (or the package link for the most current release of R). An installer will download to guide you through the installation process, which is very easy. The installer lets you customize your installation, but the defaults will be suitable for most users. I’ve never found a reason to change them. If your computer requires a password before installing new progams, you’ll need it here.

Binaries Versus Source

R can be installed from precompiled binaries or built from source on any operating system. For Windows and Mac machines, installing R from binaries is extremely easy. The binary comes preloaded in its own installer. Although you can build R from source on these platforms, the process is much more complicated and won’t provide much benefit for most users. For Linux systems, the opposite is true. Precompiled binaries can be found for some systems, but it is much more common to build R from source files when installing on Linux. The download pages on CRAN’s websiteprovide information about building R from source for the Windows, Mac, and Linux platforms.

Linux

R comes preinstalled on many Linux systems, but you’ll want the newest version of R if yours is out of date. The CRAN website provides files to build R from source on Debian, Redhat, SUSE, and Ubuntu systems under the link “Download R for Linux.” Click the link and then follow the directory trail to the version of Linux you wish to install on. The exact installation procedure will vary depending on the Linux system you use. CRAN guides the process by grouping each set of source files with documentation or README files that explain how to install on your system.

32-bit Versus 64-bit

R comes in both 32-bit and 64-bit versions. Which should you use? In most cases, it won’t matter. Both versions use 32-bit integers, which means they compute numbers to the same numerical precision. The difference occurs in the way each version manages memory. 64-bit R uses 64-bit memory pointers, and 32-bit R uses 32-bit memory pointers. This means 64-bit R has a larger memory space to use (and search through).

As a rule of thumb, 32-bit builds of R are faster than 64-bit builds, though not always. On the other hand, 64-bit builds can handle larger files and data sets with fewer memory management problems. In either version, the maximum allowable vector size tops out at around 2 billion elements. If your operating system doesn’t support 64-bit programs, or your RAM is less than 4 GB, 32-bit R is for you. The Windows and Mac installers will automatically install both versions if your system supports 64-bit R.

Using R

R isn’t a program that you can open and start using, like Microsoft Word or Internet Explorer. Instead, R is a computer language, like C, C++, or UNIX. You use R by writing commands in the R language and asking your computer to interpret them. In the old days, people ran R-Studio For Windows code in a UNIX terminal window—as if they were hackers in a movie from the 1980s. Now almost everyone uses R with an application called RStudio, and I recommend that you do, too.

R and UNIX

You can still run R in a UNIX or BASH window by typing the command:

which opens an R interpreter. You can then do your work and close the interpreter by running when you are finished.

RStudio

RStudio is an application like Microsoft Word—except that instead of helping you write in English, RStudio helps you write in R. I use RStudio throughout the book because it makes using R much easier. Also, the RStudio interface looks the same for Windows, Mac OS, and Linux. That will help me match the book to your personal experience.

You can download RStudio for free. Just Microsoft Office 2013 Crack With Product Key+Free Download 2021 the “Download RStudio” button and follow the simple instructions that follow. Once you’ve installed RStudio, you can open it like any R-Studio For Windows program on your computer—usually by clicking an icon on your desktop.

The R GUIs

Windows and Mac users usually do not program from a terminal window, so the Windows and Mac downloads for R come with a simple program that opens R-Studio For Windows terminal-like window for you to run R code in. This is what opens when you click the R icon on your Windows or Mac computer. These programs do a little more than the basic terminal window, but not much. You may hear people refer to them as the Windows or Mac R GUIs.

When you open RStudio, a window appears with three panes in it, as in Figure A.1. The largest pane is a console window. This is where you’ll run your R code and see results. The console window is exactly what you’d see if you ran R from a UNIX console or the Windows or Mac GUIs. Everything else you see is unique to RStudio. Hidden in the other panes are a text editor, a graphics window, a debugger, a file manager, and much more. You’ll learn about these panes as they become useful throughout the course of this book.

The RStudio IDE for R.

Figure A.1: The RStudio IDE for R.

Do I still need to download R?

Even if you use RStudio, you’ll still need to download R to your computer. RStudio helps you use the version of R that lives on your computer, but it doesn’t come with a version of R on its own.

Opening R

Now that you have both R and RStudio on your computer, you can begin using R by opening the RStudio program. Open RStudio just as you would any program, by clicking on its icon or by typing “RStudio” at the Windows Run prompt.

Источник: https://rstudio-education.github.io/hopr/starting.html

RStudio

OverviewAccess the RStudio IDE from anywhere via a web browserMove computation close to the dataScale compute and RAM centrallyPowerful coding tools to enhance your productivityEasily publish apps and reportsPython DevelopmentView Python data, publish and knit in Python and share objects with RAuthor and edit Python code with Jupyter Notebooks, JupyterLab and VSCodeEasily publish and share Jupyter NotebooksProject SharingShare projects & edit code files simultaneously with othersMultiple R VersionsRun multiple versions of R side-by-sideDefine environments for a particular R versionMultiple R and Python SessionsRun multiple analyses in parallelLoad BalancingLoad balance R sessions across two or more serversEnsure high availability using multiple mastersAdministrative DashboardMonitor active sessions and their CPU and memory utilizationSuspend, forcibly terminate, or assume control of any active sessionReview historical usage and server logsEnhanced SecurityLDAP, Active Directory, Google Accounts and system accountsFull support for Pluggable Authentication Modules, Kerberos via PAM, and custom authentication via proxied HTTP headerEncrypt traffic using SSL and restrict client IP addressesAuditing and MonitoringMonitor server resources (CPU, memory, etc.) on both a per-user and system-wide basisSend metrics to external systems with the Graphite/Carbon plaintext protocolHealth check with configurable output (custom XML, JSON)Audit all R console activity by writing input and output to a central locationAdvanced R Session ManagementTailor the version of R, reserve CPU, prioritize scheduling and limit resources by User and GroupProvision accounts and mount home directories dynamically via the PAM Session APIAutomatically execute per-user profile scripts for database and cluster connectivityData ConnectivityRStudio Professional Drivers are ODBC data connectors that help you connect to some of the most popular databasesLauncherStart processes within various systems such as container orchestration platformsSubmit standalone ad hoc jobs to your compute cluster(s) to run computationally expensive R or Python scriptsTutorial APIAutomate interactions with the RStudio IDERemote SessionsConnect to RStudio Workbench directly from RStudio Desktop Pro for more powerful computing resources, freeing up your local system
Источник: https://www.rstudio.com/products/rstudio/
R-Studio
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R-Undelete
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R-Drive Image
Backup, Disk Copy and System Deployment
Based on the latest hard disk image creation technologies, our R-Drive Image product creates drive image files with various compression levels on the fly without leaving Windows OS. It is one of the best solutions for system deployment, disk coping and preventing loss of your data after a fatal system failure.
R-Wipe & Clean
PC privacy and Disk Cleaning
R-Wipe & Clean protects your PC from examination, spying, or simple snooping into your off-line and Internet activities and destroys the data of those activities beyond recovery by hardware or software tools. What's more, wiping and cleaning unneeded files dramatically free up hard drive space R-Studio For Windows and speed up the system.
R-Linux
R-Linux is a free software for Windows OS and Debian/Ubuntu/Fedora/Redhat Linux platforms. This provides basic data recovery and undelete tools that can be used to recover data lost due to damaged, deleted or re-formatted partitions, virus attacks, power failures and system crashes. For a professional data recovery utility, consider R-Studio for Linux
  • R-Tools Technology Inc. is the leading provider of powerful data recovery, undelete, drive image, data security and PC privacy utilities. Our mission is to give our customers around the world the system tools to bring about a visible and substantial increase in viability, production, and ease of use at the lowest possible cost to the customer.
Источник: https://www.r-tt.com/

Set up R and R-Studio For Windows R and RStudio

R is a language for statistical computing and graphics. R’s use R-Studio For Windows the data science, econometrics and marketing communities has taken off over recent years and (at a bare minimum) should be considered as an open source replacement to Stata and SPSS.

Installing R

Watch our YouTube video, in which we walk you through the setup on Windows.

Go to the R website and download the most recent installer for your operating system.

  • Windows users: choose the “base” subdirectory, then proceed to the download.
  • Mac users: pick the release listed under “latest release” (pick the first, if it does not work, try the second).

We strongly suggest you to install R in the directory rather than the default directory.

Installing RStudio

RStudio provides an easy to work with interface to R, and its format should feel familiar to other software environments like Stata or SPSS.

Download and install the free version of RStudio for your operating system from here.

Verifying your Installation

Open RStudio from the start menu. After starting up, you should see the version corresponding to the one chosen on the website.

Screenshot of R Studio

Installing additional R Packages

You may need some additional libraries to work with R (e.g., some extra code that helps you to run your statistical analyses).

To install packages, open RStudio (if not already opened in the previous step). In the console, copy and paste the following:

  • If you are asked if you want to install packages that need compilation, type followed by. Package compilation is likely to cause some errors, and you’re all good going with packages that have already been compiled (typically, these are earlier versions of the package).
  • Wait until all the packages have been installed and the you are done. It may take a while, so be patient

Making R available on the command prompt

You have just installed R and RStudio, and learnt how to open RStudio from the start menu. However, for many of the applications that follow, you are required to access R directly from the command prompt. For example, this will enable you to run a series of R scripts in batch - which will significantly ease the burden of building complex data workflows.

Windows

For you to be able to use R from the command prompt, Windows users need to follow the steps below. On Mac and Linux, R is available from the command line by default.

Warning

Making R available via the PATH settings on Windows.

We need to update our PATH settings; these settings are a set of directories R-Studio For Windows Windows uses to “look up” software to startup.

  • Open the settings for environment variables

    • Right-click on Computer.
    • Go to “Properties” and select the tab “Advanced System settings&rdquo.
    • Choose “Environment Variables”
  • Alternatively, type “environment variable” (Dutch: omgevingsvariabelen) in your Windows 10 search menu, and press Enter.

  • Select from the list of user variables. Choose .

  • Windows 7 and 8 machines: If you chose your installation directory to be C:\R\R-4.x.x\ during your installation (i.e., you did not use the default directory), copy and paste the following string without spaces at the start or end:

  • Windows 10 machines:

    • Click and paste the following string:

      (replace by your actual version number!)

    • Click on as often as needed.

Warning

Making R available via the PATH settings on Mac/Linux

  • Paste this command in your terminal:
  • Add the following two lines archicad student it:
Tip

Keep in mind that after you add a new directory to the variable, you need to start a new command prompt/terminal session to verify whether it worked. Sometimes it may take a couple of minutes until your PATH is recognized by the terminal.

Now PDF Shaper Professional 11.8 + Crack Premium [ Latest ] verify whether we can open R from the command prompt

Open the command prompt/terminal and enter:

followed by pressing. The expected return begins with:

Great job - you’ve managed to install R and configure it for use for data-intensive projects!

Making R find packages on the command prompt

You can now access R directly from the command prompt. Nevertheless, code that runs R-Studio For Windows on R Studio might return on the command prompt.

Why is that? Sometimes, when running R from the command line, it doesn’t find the packages that were installed in your user library paths.

Solution: Tell R where to find your user library.

Warning

Making R find your user library via the PATH settings on Windows.

  • In RStudio, type and note the path to your user directory (typically the one that contains your user name).

  • Open the settings for environment variables

    • Right-click R-Studio For Windows Computer.

    • Go to “Properties” and select the tab “Advanced System settings&rdquo.

    • Choose “Environment Variables”

  • Select and name it. is the path (that you previously noted) to your user directory.

  • Check whether only specifies your allocated user directory by typing into a new RStudio session.

Rather want to set on a Mac or Linux machine? Read more here.

Verify that you can access your packages

Close all command prompts/terminals. Open one again, type to open R and then enter:

Note that the command requires you to specify the package name without quotation marks (e.g.,not).

Expect a return beginning with:

Get an error message? Try reinstalling the package using .

Источник: https://tilburgsciencehub.com/building-blocks/configure-your-computer/statistics-and-computation/r/
R-Studio For Windows

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R-Studio For Windows

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