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Mind your R-Language


R is a programming language and environment, which is used for computational statistics and graphics. A GNU project developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues, similar to the S language and environment. A different form of implementation of S language can be considered as R language.

Providing a wide variety of statistical, like linear & non-linear modeling, time series analysis, clustering, classification and graphical techniques, R language is highly extensible. Even though the S language is more often the choice for research in statistical approach, R language, on the other hand, provides an Open Source direction to participation in an activity.

R has its strength in producing a well-designed broadcast quality plot with an ease, which includes symbols of mathematics and formulas where it is needed. The user at the end retains full control, with the defaults for minor design choices in graphics been taken care of.

Available as Free Software it compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.

Why R Language?

Ease with data analysis techniques

Every data manipulation, chart and a statistical model that the modern data scientist could ever need, R language virtually includes all of them. Finding, downloading and using cutting edge reviewed methods in statistics and predictive modeling from leading researchers in data science is easy and free of charge.

Creating appealing and unique data visualizations

It has always been an essential part of data analysis to have to represent complex data with charts ad graphs. R goes way beyond traditional line plot and bar chart. Drawing meaning from multidimensional data with multi-panel charts, 3-D surfaces is easy being heavily influenced by thought leaders in data visualization like Bill Cleveland and Edward Tufte. Many of the stunning infographics seen in the Economist, FlowingData blog, The New York Times are the result of custom charting capabilities of R.

Better Faster Results

Not following the stereotyped point-and-click menus or inflexible “black-box” procedures, R is a programming language designed precisely for data analysis. Creating data analysis is faster by the intermediate R language users than the users of traditional statistical software, with the flexibility to mix and match models for the better results. Automation of the R scripts is easy, promoting both production deployments and reproducible research.

Talents of Data Scientists drawn from worldwide

A community of more than 2 million users and thousands of developer worldwide support R language as a thriving open source project. Whether you're using R to optimize portfolios, analyze genomic sequences, or to predict component failure times, experts in every domain have made resources, applications, and code available for free, online.

R language includes:

  • a large, coherent, integrated collection of intermediate tools for data analysis,

  • including conditionals, loops, input & output facilities and user-defined recursive functions, R language is a well developed and effective programming language

  • effective storage and handling facility

  • in particular matrices, operator for calculations on arrays

  • both flexible and powerful programming language

  • operates with the problems the way it is to be thought about.

R is not just a statistics package. It is a language. It is an integrated suite of software facilitating for graphical display, calculation, and data manipulation.

#rlanguage #programming #GNUlanguage #statisticalcomputing

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