- R is a programming language and software environment for statistical analysis, graphics representation, and reporting.
- R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand.
- R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows, and Mac.
- R is free software distributed under a GNU-style copyleft and an official part of the GNU project called GNU S.
- The core of R is an interpreted computer language that allowed branching and looping as well as modular programming using functions.
- R allows integration with the procedures written in the C, C++, .Net, Python or FORTRAN languages for efficiency.
Features of R Programming.
- R is a Well developed, simple, and effective programming language.
- R has an effective data handling and storage facility.
- R provides a suite of operators for calculations on arrays, lists, vectors, and matrices.
- R provides a large. coherent and integrated collection of tools for data analysis.
- R provides graphical facilities for data analysis and display either directly at the computer or the printing at the papers.
What R does.
- Data handling and storage e.g. numeric, textual.
- We can handle matrix algebra.
- Hash tables.
- High -level data analytic and statistical functions.
- Deal with classes ("Object-Oriented Programming").
- Provides graphics.
- Programming language: loops, branching, subroutines.
What R does not
- Is not a database, but connects to DBMSs.
- Has no graphical user interfaces, but connects to java.
- Language interpreter can be very slow but allows to call own C/C++ code.
- No spreadsheet view of data, but connects to Excel/Ms-Office.
- No professional/commercial support.
Advantages of R
- R is free and open-source software.
- R has no License restrictions.
- R has over 4800 packages available from multiple repositories specializing in topics like econometrics, data mining, spatial analysis, and bio-informatics.
- R is cross-platform.
- R plays well many other tools, importing data, for example, for CSV, SAS, and SPSS, or directly from Microsoft Excel, Microsoft Access, Oracle, MySQL, and SQLite.
- It can also produce graphics output in PDF, JPG, PNG, and SVG formats, and the table output for LaTex and HTML.
Disadvantages of R
- Average memory performance because of poor management of large datasets and complicated structure of packages in R
- Average computing performance because no default parallel execution
- Difficult data visualization and management because inspect of dataset is difficult.
- Relatively difficult to learn due to complex data structures.
- Not more helpful in real-time data analysis.
