Pros and Cons of R Programming Language

Here, we are going to discuss about the various pros and cons of R programming language.
Submitted by Bhavya Sri Khandrika, on May 02, 2020

In general, the R programming language is considered as the machine learning language. This is widely employed in the applications where the data analysis, visualization, and the sampling process are involved. The R programming language is taken as the free program and is, of course, an open-source program too. The R program is extensively used in various applications since it endorses the multiple platforms that may run on several operating systems. The R programming language is largely suitable for the statistical calculations and also helps in creating the functions that are associated with the mathematical analysis. Of course, a programming language is something that evolves continuously and undergoes various changes as time passes and the requirements of the people vary. In this particular article let us concentrate on the various pros and cons of the R language. As of now, the R language is encountering several challenges and thus in the future, most of the cons will turn to eliminate, and finally, the R language will be seen as the superior in the coding world.

Coming to the pros section the R programming language has the following advantages over the other programming languages.

Pros of R Language

1) Extremely easy to code

Since the R language is very easy to code therefore the R language is broadly used in several applications. Usually, the users feel very comfortable during the installation process and configuration of the R language in one's system. Thus, the programmers see this particular language as their favorite due to the user-friendly platform provided by the R programming language.

2) Integration with the other programming languages

R allows the users or the programmers to incorporate the R language with the other programming languages like C, C++, Python, and Java. Also for this purpose, the users can use various data sources to accomplish this purpose.

3) Effective Statistical Tool

The R language is considered as one of the most extensive and effective mechanisms that enable the programmers to work practically on the Statistical details. It is used in the statistical computations and in the analysis part.

4) Open-source program

The team of R enabled the users to feel comfortable while working on the R platform. Also, the R language can be easily downloaded and installed on any PC of an individual.

5) Powerful

The R language is encompassed with multiple techniques that provide the users with a relaxed environment where they can code and bring the result practically to any problem. This particular tool is widely employed for the sampling process, data analysis, and visualization. However, the R language must be appreciated as it contains several techniques involved in it where they are used in dealing with the analysis of the statistical data.

6) State of the art

The R language is always well seen as a treasure as it contains the various procedures involved in it that eventually assist the users in developing the best algorithms for given real-time problems. Initially, the programmers can use the R for developing satisfactory algorithms for the problems and then later these algorithms can be run on various operating systems for better results. Actually, once the algorithms are ready then the programmers make those algorithms into inbuilt packages in the R language. Thus one can easily access these packages in the R environment when compared to the other programming languages.

7) Cross-platform

Often the programmers who work on the R confess that the R enables them with a comfortable platform to work upon. Also, many programmers say that the R language is the platform-independent as it works in every other version like GNU/Linux or in Windows i.e., irrespective of the type of the operating system the R language gives the same consistent results.

8) Open for modifications

The team of the R language is quite more kind as they give the opportunity to every programmer to fix the bugs if possible, also they can include various other packages that will make the users more pleased to work with R. Everyone is welcome to create a new code or enhance the code of the existing packages in order to boost the functionality of the R compiler.

9) Multiple libraries

Programmers who work with the R environment are more satisfied with the inbuilt options or functions and other attributes available in it. In addition to that one can also find several sources in the corresponding webpages and can easily develop algorithms for their problems. The different libraries available here in the R language assist the programmers in coming up with the best solution to real-time problems.

Now it's the time to learn about the various cons available in the R programming language.

Cons of R Language

1) Little consistency in the algorithms

The users encounter a situation where they face problems while working with the existing algorithms that are written in other packages. In this, the programmers will trouble themselves while working with the existing algorithms and in the process of trying to bind them to their current programs. Also one may determine the inconsistency available in the software also because of this reason.

2) Time-consuming

In case if the user wishes to utilize the existing codes which are in the packages then he or she needs to spend more time thinking about the ways how these existing codes will fit their problem perfectly. Thus all this procedure kills the time and that may bring loss to the users who work upon this.

3) Decentralized packages

We all are acquainted with the fact that the algorithms are associated with multiple numbers of packages. Hence this will create a problem for the users while working with a project. This is because the programmers may get perplexed about the exact position of algorithms i.e., which package consists of this particular algorithm that he or she wants to use in their program.

4) Incomplete documentation

The documentation which is generally present in the algorithms is of course partially incomplete. Moreover, there will not be any practical examples that demonstrate the usage of the existing algorithms on the canonical problems available to the users.

5) The complexity of algorithms

One will face the issues when he or she needs to work with the algorithms that are already available to them beforehand. But the problem pertains when they need to bind the existing codes with the new ones. Because the complexity of the codes change when there is a change in the packages, that means as the packages are changed then the complexity of the codes or algorithms written in them vary respectively.

6) Recapturing of intensive language:

One of the major disadvantages of working with the R is that it consumes a lot of memory of the system. Because of this reason generally, the R language is treated as the memory dependent and thus it inundates all the accessible memory space in the space. In addition to the above-stated point, there is one more thing to be noted regarding the R programming language. The commands that are used in the R language may influence the memory administration operation that is available in every system.

7) Aboriginal R is sluggish than its central competitor

Every programmer who works on the R environment mainly complains about a single issue. The prime demerit of using the R language is whatever the packages written in the R programming language are more sluggish than the codes written in the Matlab or other programming languages like Python.

8) Ingenious programming language

The R programming language is very flexible. Therefore the programmers need to be very careful while working with the codes. If they tend to lose their control over the codes they have written then the codes may turn complex and ultimately make the programmers suffer because of them.

The above points have completely dealt with both sides of using the R language. Since the world is experiencing various changes in terms of the advancements and further inventions, this in due course of time the cons will turn themselves into pros after keen observation and research on the R language.



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