What Are The Features Of R Programming?
What Are The Features Of R Programming?
R has a lot of capabilities for data scientists and analytics. These distinguishing characteristics distinguish R from the crowd of statistical languages:
1)R Is Open Source
R is a programming environment that is free and open source. It is free and can be customised and adapted to meet the user’s and the project’s needs.
You can make modifications and add packages to add new features.
R is available for free. You may learn to install R, download it, and begin practising now.
2)Strong Graphic Capability
R can generate static graphics with high-quality visualisations and has expanded libraries that enable interactive graphics.To know more about the graphic capability join R Programming Online Course.
This greatly simplifies data visualisation and data representation.
R can create everything from simple charts to complex and interactive flow diagrams. Take a look at R’s visually appealing graphical visualisations.
3)Comprehensive Environment
R has a reasonably extensive development environment, which may be used for statistical computing and software development.
R is an object-oriented programming language. It also includes a powerful package called Rshiny that can be used to create full-fledged web apps.
In conjunction with data analysis and visualisation, R can be used to create highly interactive online data-driven storytelling.
4)Disturbed Computing
Tasks are dispersed across numerous processing nodes in distributed computing to minimise processing time and boost efficiency.
R offers tools like ddR and multiplies, allowing it to process big data sets using distributed computing.
5)Running A Code Without A Compiler
R is an interpreted language, which implies that it does not require a compiler to generate code. R interprets supplied code directly into lower-level calls and pre-compiled code.
6)Data Wrangling
The process of cleansing large and inconsistent data sets to facilitate computation and further analysis is known as data wrangling. This is a time-consuming process.
R’s broad tool collection can be utilised for database management and wrangling.
7)Compatability With Other Data Processing Technologies
R works well with further data processing and distributed computing technologies such as Hadoop and Spark. Using a Spark cluster remotely is feasible to process large datasets in R.
R and Hadoop can also be used together to combine Hadoop’s large-scale data processing and distribution capabilities with R’s statistical computing capacity.
Conclusion:
I hope this article will let you know about the features of r programming. To know more about R programming join R Programming Training In Chennai at FITA Academy.Thus the features of R Programming are open source, strong graphic capability, comprehensive environment, disturbed computing, running code without compiler, data wrangling and compatibility with other data processing technologies.