R for Windows is a GUI for writing code in R language and performing the statistical and graphical analysis. With advancement in technologies such as BIG DATA, Data Analytics, and Data Science, it has become imperative for new and old organizations to drive growth based on the customer data. To make sense of this data, it is necessary to analyze it first. That is where R plays a major role. But here I am not going to discuss what R is, rather I am going to discuss R for Windows software.
If you’re going to perform analysis on huge quantities of data or even small population samples, you need a software that can handle all the data well. R for Windows a software for this task. This program features a console window where you can write your code and the entire interface is intuitive and easy to use and requires minimum effort in performing tasks such as printing your code, saving and loading workspace, stopping and starting computation. However, I recommend using R-Studio that adds an additional layer over R for Windows to manage data better.
To help you get acquainted with the software, the developers have built in manuals. You can update, load and install packages directly through the console. You can also customize the GUI based on your requirements. You customize aspects such as pager style, font, rows, columns and GUI’s color and font. You can also save your written codes in form of scripts. This makes your code portable and you can run your code on R software on any other system.
To sum up, R for Windows is a must have software if you deal in statistical analysis. I recommend this software to all Data Science and Data Analytics professionals.
v3.2 [Apr 18, 2015]
FEATURES
- utf8ToInt() now checks that its input is valid UTF-8 and returns NA if it is not.
- install.packages() now allows type = "both" with repos = NULL if it can infer the type of file.
- nchar(x, *) and nzchar(x) gain a new argument keepNA which governs how the result for NAs in x is determined. For the R 3.2.x series, the default remains FALSE which is fully back compatible. From R 3.3.0, the default will change to keepNA = NA and you are advised to consider this for code portability.
- news() more flexibly extracts dates from package ‘NEWS.Rd’ files.
- lengths(x) now also works (trivially) for atomic x and hence can be used more generally as an efficient replacement of sapply(x, length) and similar.
- The included version of PCRE has been updated to 8.37, a bug-fix release.
- diag() no longer duplicates a matrix when extracting its diagonal.
- as.character.srcref() gains an argument to allow characters corresponding to a range of source references to be extracted.
Feature-rich relational database known for its high performance and excellent concurrency
