Install Packages from Repositories or Local Files. Character, indicating the type of package to download and install. R packages are primarily distributed as source packages, but binary packages (a packaging up of the installed package) are also supported, and the type most commonly used on Windows and by the CRAN builds for macOS. This R package queries download stats of R packages. For CRAN packages, it queries from RStudio download logs. For Bioconductor packages, it queries from. Installing R packages. November 6, 2010. Which server should you use to download the package. Every time you install a R package, you are asked which. Installling R packages on Windows Select 'install packages(s) from local zip files', under the 'Packages' pull-down menu, as below: There is a message about it being successful - but one can always load the package explicitly to check.
- Download and install a package (you only need to do this once). To use the package, invoke the library( package ) command to load it into the current session. (You need to do this once in each session, unless you customize your environment to automatically load it each time.).
- Installing R Packages. Jeffrey Leek Johns Hopkins Bloomberg School of Public Health. When you download R from the Comprehensive R Archive Network (CRAN), you get that ``base' R system. The base R system comes with basic functionality; implements the R language.
- [Voiceover] If you're going to start using Ras the basis for your statistical analyseswhether in addition to Excel or to use it in place of Excel,you're going to need to have the R software downloadedonto your computer.And that's what this lesson is going to be about.Before we actually start doing that though,I want you to learn something a little bit moreabout the system that you're using.If you come down to the lower left cornerof your window and click the Start menu,assuming that you're using Windows 10,you'll get this window.
If you're using something such as Windows 8,you might have a charms bar at the right edgeof your screen.And either way, you're gonna want to come downto Settings and then click System.And notice in the navbar on the left sideof the screen, there's an About link,and you can click that.And once it has responded with a new windowor a new pane, you can notice the system type entryunder PC at the top of the screen.
And this particular system is a 64-bit operating system.Make a note of whether it's a 64-bit systemon your computer or a 32-bit systembecause that will have some implicationsfor just how you go about installing R.Once you have that information about the typeof system that you are using, you're going to wantto use a browser to get to this website here.It's named cran.r-project.org,and that's kind of a cryptic way of sayingthe Comprehensive R Archive Network.
And once you've gotten there,you have some choices for download.You could download R for Linux, R for the Mac,or R for Windows.I'll go ahead and use the Download R for Windowsin this case.And we simply click that optionand we get to R's subdirectories,one of which is Base.Now R comes with a Base system which has some degreeof statistical functionality built into itand quite a bit of data handling functionality.That's what we'll be downloading to begin with.
You get the rest of R from the contributed packages,and we'll be getting to those later onin this series of lessons.At this point, you want to click install Rfor the first time at a link locatedin the upper righthand corner of your screen.So I'll click that now,and we get to the download page.The option that we're going to selectis Download R 3.3.0 for Windows.That's the current release as of the timethat I'm recording this.By the time that you're viewing it,they will probably have come out with a different release,and so it won't say 3.3.0 but something else.
That's nothing to worry about,perfectly natural and normal.You can also go to some of these frequently asked questionsavailable on this page if you want to checkon whether or not R runs on the particular versionof Windows that you're running, for example.But at this point, we'll just clickDownload R 3.3.0 for Windows.And the download starts, and it's going to takea few seconds to complete.And when it is completed, we can go aheadand click on that button.And at this point you may run into a windowthat asks you to authorize the installation of R.
And you can go ahead and click yes.If that doesn't work for you for some reason,you'll probably want to get in touchwith your tactical support staff to make surethat the version of the operating systemthat you're running will accept Rand allow it to be installed.We're going to use the default command herefor English as the language for the installation.At this point, we have a brief wizard,a fairly standard one for installation.And I'm going to choose options which installthe default selections.
But go ahead and take the time to examinethe information that's presented to youand make whatever choices seem most appropriatefor your situation.But I'll go ahead and click Next nowand it'll bypass the public license.And I'm going to accept the default installation folderand click Next.At this point, you have a decision to make.If you're running a 64-bit system,then you will want to include the 64-bit files.If you're not running a 64-bit system,if you're running a 32-bit system,you may as well go ahead and clear that box.
That it, at the very least, save you a little bitof disk space.The issue here is how much memory that R can access.And if you're going to be pumping huge amountsof data through R, and you have a 64-bit system,you'll probably want to accept it.But for the time being, I'm going to go aheadand clear that box and click the next step.And yeah, we'll go ahead and accept the defaults.And we'll want the shortcut in the Start menu folder.We'll also want to create a quick launch iconas well as the Desktop icon.
And click Next.And now the installation goes aheadand does all the extraction of the files for Windows.This really only takes a few seconds.And we click Finish to exit setup.And at this point, we can go back to the Desktop.There's our link to R and up comes the R Console.You'll be seeing a lot of this Consoleover the next few lessons.And now with the link to R on the Desktop,we could just double-click itand up comes the R Console.And you'll be ready to start processing in R.
One of the reasons to use R for analysis and visualization is the rich ecosystem of ‘packages’ contributed by others. In most cases, just as with smartphones, “There’s a package for that.” If you want to be efficient you need to embrace other people’s work and in the case of R that means installing packages. This post walks you through the basics of package installation and use and gives some tips on workarounds when a package won’t install.
Simple example
For the impatient lets start off with a simple example. In this example (on Ubuntu Linux) we’ll run R as the superuser so that packages will be installed in the default location. We will install the “geonames” package and then show off the new functionality we just added.
If you don’t run R as superuser you won’t have permission to write packages into the site-library and you will be prompted to create a personal library. You can specify the library, repository and a few other options by passing parameters to the install.packages()
method. Use ?install.packages
to learn more.
So what extra functionality does this new “geonames” package bring? You’ll have to do a little reading to figure out the details but for now just paste these lines into your R session:
Here is the result:
Who’d-a-thunk that R could so easily be turned into a real time weather system?
CRAN
In order to install and make use of packages you first have to find them. Luckily, most (but not all) R packages are organized and available from CRAN — the Comprehensive R Archive Network. Just click on the Packages link to see the full list of contributed packages. Packages are listed alphabetically with a short description. Unfortunately, there is no rating system but you can get a quick sense of quality by clicking on a package link and looking at the “Published” date and especially any “Reverse dependencies” listed at the the bottom of a package. Reading the documentation and looking at the number of releases in the “Old sources” is also very helpful.
CRAN also maintains a set of Task Views that identify all the packages associated with a particular task. The maintainers of these views do a generally excellent job of staying on top of their area of interest and giving a detailed summary of which packages do what. If one of the task views is a perfect match you can have R install every package from that view using the “ctv” package. Yes, “ctv” is a package to automate package installation. See the section below on “Installing older versions” if you have trouble installing “ctv”.
How To Download Car Package In R
Installing packages
The basics of package installation are given in chapter 6 of R Installation and Administration. There are two ways to do a command line installation of packages: from the R command line and from the shell command line.
Within R you can use install.packages()
as demonstrated in the example above. This will always attempt to install the latest version of packages it knows about.
You can also invoke R from the command line. This is useful for some packages when install.packages()
doesn’t work or for packages that are not part of CRAN. More information is available with R CMD INSTALL --help
. To install packages this way you must first download the package source to your local machine. Here is a quick demonstration:
Installing older versions
If you have total control over your system and always keep it at the bleeding edge then you will have no problem installing the latest and greatest versions of R packages. However, if your version of R is older (Perhaps you are running R on a webserver with CentOS?) then some of the more recent releases of packages will not work and install.packages()
will generate messages like:
This is when you have to poke around in the “Old sources” link on the CRAN page for that package and use trial-and-error to find an older version of the package that will work with your version of R. You should start by determining what version of R you have:
Given that our version of R was released at the end of 2008, any version of the “sp” package released in 2008 should definitely work. At least some of the 2009 releases should also work. Perusing the sp archive, we might try installing version 0.9-37, the last of the 0.9-3x series which was released in May of 2009:
Using packages
To use a package you start up R and load packages one at a time with the library() command.
Over time, your package library will contain more and more packages. Or perhaps system administrators or other users have also installed packages. It’s good to know what’s installed and at what version. This is where the location of the package library comes in handy. If you poke around you will find out that most packages come with a DESCRIPTION file that contains that information. To see all the package versions on our Ubuntu system we could just type:
R Package Download Windows
Of course there is also an ‘R’ way of getting this information. All of the fields in DESCRIPTION files are accessible through the installed.packages() command (note the spelling) which returns a matrix of information with packages as row names and fields as column names. The following example shows how to access this information programmatically from within R:
Special Cases
ncdf
The ncdf package requires that NetCDF — including the development libraries — first be installed on your system. Unfortunately, the NetCDF libraries and include files are not installed in a uniform location across Unix systems. This is a case where we need to pass configuration arguments to R CMD INSTALL. Here is what ended up working on Ubuntu 10.04 LTS:
And for anyone stuck on CentOS 5.x:
Here’s an August, 2013 update for CentOS 6.x:
Problems
Not every package will install automatically. For error messages and workarounds please see the post on Package Installation Problems.