Tag: installr

R 3.2.0 is released (+ using the installr package to upgrade in Windows OS)

R 3.2.0 (codename “Full of Ingredients”) was released yesterday. You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below.

Upgrading to R 3.2.0 on Windows

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code:

# installing/loading the latest installr package:
install.packages("installr"); library(installr) #load / install+load installr

updateR() # updating R.

Running “updateR()” will detect if there is a new R version available, and if so it will download+install it (etc.).

I try to keep the installr package updated and useful, so if you have any suggestions or remarks on the package – you are invited to leave a comment below.

CHANGES IN R 3.2.0:

As always, David smith mentioned in his post some of the main changes, writing how many of the changes in this release have happened behind the scenes to improve R’s engine for performance and reliability. These include:

  • A number of fixes proposed by Radford Neal, bringing some of the performance improvements of pqR to R while maintaining backwards compatibility.
  • more progress in handling big in-memory data objects (for example, you can now cbind/rbind matrices with more than 2 billion elements).
  • some significant updates to R’s byte compiler with new instructions that allow many scalar subsetting and assignment and scalar arithmetic operations to be handled more efficiently. This can result in significant performance improvements in scalar numerical code.
  • the package-checking system now does a more thorough job of making sure contributed packages comply with CRAN policies.

And here is also the full list of new features, bug fixes, etc:

Continue reading “R 3.2.0 is released (+ using the installr package to upgrade in Windows OS)”

R 3.1.3 is released (+ easy upgrading for Windows users with the installr package)

R 3.1.3 (codename “Smooth Sidewalk”) was released today. You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below.

Upgrading to R 3.1.3 on Windows

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code:

# installing/loading the latest installr package:
install.packages("installr"); library(installr) #load / install+load installr

updateR() # updating R.

Running “updateR()” will detect if there is a new R version available, and if so it will download+install it (etc.).

I try to keep the installr package updated and useful, so if you have any suggestions or remarks on the package – you are invited to leave a comment below.

CHANGES IN R 3.1.3:

As always, David smith mentioned in his post some of the main changes, writing:

As has become usual in March, this release is primarily for minor bugs and improvements in R, as the development switches focus to the next major release (R 3.2.0 is expected on April 16). Improvements include: ability to download files greater than 2GB on 32-bit builds; better handling of complex (imaginary) numbers for several functions; improved command completion in the Windows GUI; and improved performance when using S4 classes. (See the complete list here.)

And here is also the full list:

Continue reading “R 3.1.3 is released (+ easy upgrading for Windows users with the installr package)”

R 3.1.2 release (and upgrading for Windows users)

R 3.1.2 (codename “Pumpkin Helmet“) was released last week. You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below.

Upgrading to R 3.1.2 on Windows

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code:

# installing/loading the latest installr package:
install.packages("installr"); library(installr) #load / install+load installr

updateR() # updating R.

Running “updateR()” will detect if there is a new R version available, and if so it will download+install it (etc.).

I try to keep the installr package updated and useful, so if you have any suggestions or remarks on the package – you are invited to leave a comment below.

If you use the global library system (as I do), you can run the following in the new version of R:

source("https://www.r-statistics.com/wp-content/uploads/2010/04/upgrading-R-on-windows.r.txt")
New.R.RunMe()

CHANGES IN R 3.1.2:

David smith mentioned in his post some of the main changes, writing:

[…] improvements for the log-Normal distribution function, improved axis controls for histograms, a fix to the nlminb optimizer which was causing rare crashes on Windows (and traced to a bug in the gcc compiler), and some compatibility updates for the Yosemite release of OS X on Macs.

And here is also the full list:

Continue reading “R 3.1.2 release (and upgrading for Windows users)”

R 3.1.1 is released (and how to quickly update it on Windows OS)

R 3.1.1 (codename “Sock it to Me“) was released today! You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below.

Upgrading to R 3.1.1 on Windows

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code:

# installing/loading the latest installr package:
install.packages("installr"); require(installr) #load / install+load installr

updateR()

After running “updateR()”, the function will detect that R is available for you, and will download+install it (etc.).

Note that the latest installr version (0.15.3) was released just less than a month ago to CRAN, and it is recommended to upgrade to it, since it has more updated URLs to some software.
I try to keep the installr package updated and useful, so if you have any suggestions or remarks on the package – you are invited to leave a comment below.

If you use the global library system (as I do), you can run the following in the new version of R:

source("https://www.r-statistics.com/wp-content/uploads/2010/04/upgrading-R-on-windows.r.txt")
New.R.RunMe()

CHANGES IN R 3.1.1:

David smith gave a nice summary of the features here. And here is also the full list:

NEW FEATURES

Continue reading “R 3.1.1 is released (and how to quickly update it on Windows OS)”

R 3.1.0 is released!

R 3.1.0 (codename “Spring Dance“) was released today!

hora jump
Photo credit: The Batsheva Dance Company in Ohad Naharin’s Hora. Photo by Gadi Dagon.

You can get the source code from
https://cran.r-project.org/src/base/R-3/R-3.1.0.tar.gz

or wait for it to be mirrored at a CRAN site nearer to you. Binaries for various platforms will appear in due course.

The full list of new features and bug fixes is provided below.

Upgrading to R 3.1.0

You can download the latest version from here.

If you are using Windows, it might take another 24 hours until you could update R. For convenience, you can upgrade to the latest version of R using the installr package. Simply run the following code:

# installing/loading the latest installr package:
install.packages("installr"); require(installr) #load / install+load installr

updateR()

After running “updateR()”, the function will detect that R is available for you, and will download+install it (etc.).

Note that the latest installr version (0.14.0) was released a week ago to CRAN, and it is recommended to upgrade to it, since it is now more robust for various extreme cases of upgrading R.
I try to keep the installr package updated and useful, so if you have any suggestions or remarks on the package – you are invited to leave a comment below.

If you use the global library system (as I do), you can run the following in the new version of R:

source("https://www.r-statistics.com/wp-content/uploads/2010/04/upgrading-R-on-windows.r.txt")
New.R.RunMe()

CHANGES IN R 3.1.0:

NEW FEATURES

Continue reading “R 3.1.0 is released!”

R 3.0.3 is released

R 3.0.3 (codename “Warm Puppy) was released several days ago. The full list of new features and bug fixes is provided below.

Upgrading to R 3.0.3

You can download the latest version from here. Or, if you are using Windows, you can upgrade to the latest version using the installr package. Simply run the following code:

# installing/loading the package:
if(!require(installr)) {
install.packages("installr"); require(installr)} #load / install+load installr

updateR()

I try to keep the installr package updated and useful. If you have any suggestions or remarks on the package, you’re invited to leave a comment below.

If you use the global library system (as I do), you can run the following in the new version of R:

source("https://www.r-statistics.com/wp-content/uploads/2010/04/upgrading-R-on-windows.r.txt")
New.R.RunMe()

CHANGES IN R 3.0.3:

NEW FEATURES

Continue reading “R 3.0.3 is released”

R-users.com: invite fellow R-users to Jobs, conferences, and R-projects

Dear R users,

I am happy to officially announce a new website called R-users.com. The idea of the site is that community members will invite other R users to join them in their R projects, conferences, and work places.

R-users_homepage_screeshot

This site is a “job board” for R users, hosting various “call to action” to R-users, to do stuff such as:

  1. Join a open-source or paid projects of R programming
  2. Send/give a presentation for conferences (on R, statistics, machine learning, data science, etc.)
  3. Apply to be a student/researcher in an academic institution
  4. And other “R jobs”

For example, I am the author of the R package “installr” for easily updating R on windows. However, I would love for someone who is a mac/linux user to expend my package for non-Windows users. Hence, I created a new “job”, inviting help on this project, which you may see in this link.

If you also wish to post your own “R job” for other R-users to see, here is a very short presentation on how to do it:

The basic steps are:

  1. Register/login to the site (you can use your facebook/gmail account with just one click-registration)
  2. Fill in your proposed project/job details
  3. That’s it!

I intend to promote this site on r-bloggers.com, please help me in promoting this site on facebook and your own websites – so that more of us will be able to work together.

Yours,
Tal Galili

R 3.0.2 and RStudio 0.9.8 are released!

R 3.0.2 (codename “Frisbee Sailing”) was released yesterday. The full list of new features and bug fixes is provided below.

Also, RStudio v0.98 (in a “secret” preview) was announced two days ago with MANY new features, including:

Upgrading to R 3.0.2

You can download the latest version from here. Or, if you are using Windows, you can upgrade to the latest version using the installr package (also available on CRAN and github). Simply run the following code:

# installing/loading the package:
if(!require(installr)) {
install.packages("installr"); require(installr)} #load / install+load installr

updateR(to_checkMD5sums = FALSE) # the use of to_checkMD5sums is because of a slight bug in the MD5 file on R 3.0.2. This issue is already resolved in the installr version on github, and will be released into CRAN in about a month from now..

I try to keep the installr package updated and useful. If you have any suggestions or remarks on the package, you’re invited to leave a comment below.

If you use the global library system (as I do), you can run the following in the new version of R:

source("https://www.r-statistics.com/wp-content/uploads/2010/04/upgrading-R-on-windows.r.txt")
New.R.RunMe()

p.s: you can also use the installr package to quickly install the new RStudio by using:

# installing/loading the package:
if(!require(installr)) {
install.packages("installr"); require(installr)} #load / install+load installr

install.RStudio()

Continue reading “R 3.0.2 and RStudio 0.9.8 are released!”

Top 100 R packages for 2013 (Jan-May)!

What are the top 100 (most downloaded) R packages in 2013? Thanks to the recent release of RStudio of their “0-cloud” CRAN log files (but without including downloads from the primary CRAN mirror or any of the 88 other CRAN mirrors), we can now answer this question (at least for the months of Jan till May)!

By relying on the nice code that Felix Schonbrodt recently wrote for tracking packages downloads, I have updated my installr R package with functions that enables the user to easily download and visualize the popularity of R packages over time. In this post I will share some nice plots and quick insights that can be made from this great data. The code for this analysis is given at the end of this post.

Top 8 most downloaded R packages – downloads over time

Let’s first have a look at the number of downloads per day for these 5 months, of the top 8 most downloaded packages (click the image for a larger version):

top_8_R_Packages_over_time

We can see the strong weekly seasonality of the downloads,  with Saturday and Sunday having much fewer downloads than other days. This is not surprising since we know that the countries which uses R the most have these days as rest days (see James Cheshire’s world map of R users). It is also interesting to note how some packages had exceptional peaks on some dates. For example, I wonder what happened on January 23rd 2013 that the digest package suddenly got so many downloads, or that colorspace started getting more downloads from April 15th 2013.

“Family tree” of the top 100 most downloaded R packages

We can extract from this data the top 100 most downloaded R packages. Moreover, we can create a matrix showing for each package which of our unique ids (censored IP addresses), has downloaded which package. Using this indicator matrix, we can thing of the “similarity” (or distance) between each two packages, and based on that we can create a hierarchical clustering of the packages – showing which packages “goes along” with one another.

With this analysis, you can locate package on the list which you often use, and then see which other packages are “related” to that package.  If you don’t know that package – consider having a look at it – since other R users are clearly finding the two packages to be “of use”.

Such analysis can (and should!) be extended. For example, we can imagine creating a “suggest a package” feature based on this data, utilizing the package which you use, the OS that you use, and other parameters.  But such coding is beyond the scope of this post.

Here is the “family tree” (dendrogram) of related packages:

Family_tree_of_Top_100_R_Packages

To make it easier to navigate, here is a table with links to the top 100 R packages, and their links:

Continue reading “Top 100 R packages for 2013 (Jan-May)!”

R 3.0.1 is released

R 3.0.1 (codename “Good Sport”) was released last week. As mentioned earlier by David, this version improves serialization performance with big objects, improves reliability for parallel programming and fixes a few minor bugs.

Upgrading to R 3.0.1

You can download the latest version from here. Or, if you are using windows, you can upgrade to the latest version using the installr package (also available on CRAN and github). Simply run the following code:

# installing/loading the package:
if(!require(installr)) {
install.packages("installr"); require(installr)} #load / install+load installr

updateR(to_checkMD5sums = FALSE) # the use of to_checkMD5sums is because of a slight bug in the MD5 file on R 3.0.1. Soon this should get resolved and you could go back to using updateR(), install.R() or the menu upgrade system.

I try to keep the installr package updated and useful. If you have any suggestions or remarks on the package, you’re invited to leave a comment below.

If you use the global library system (as I do), you can run the following in the new version of R:

source("https://www.r-statistics.com/wp-content/uploads/2010/04/upgrading-R-on-windows.r.txt")
New.R.RunMe()

Continue reading “R 3.0.1 is released”