All about the R programming language

In this article, we introduce the R programming language; From the reasons for learning to the advantages and disadvantages of using this language, it will be explained briefly but very useful. We have introduced their help, start their learning process. But in this article, the goal is to introduce one of them; R programming language is one of the most popular programming languages that has many enthusiasts and is extremely useful in the world of science and technology. If you have heard the name of this programming language but do not know much about what it is, its advantages and disadvantages, it is recommended to follow this article to the end. In this article, we will discuss the following 4 things:

BingMag.com All about the R programming language

In this article, we introduce the R programming language; From the reasons for learning to the advantages and disadvantages of using this language, it will be explained briefly but very useful. We have introduced their help, start their learning process. But in this article, the goal is to introduce one of them; R programming language is one of the most popular programming languages that has many enthusiasts and is extremely useful in the world of science and technology. If you have heard the name of this programming language but do not know much about what it is, its advantages and disadvantages, it is recommended to follow this article to the end. In this article, we will discuss the following 4 things:

  • What is the R programming language?
  • Is R easy to learn and use?
  • Should we use R programming language?
  • Advantages and disadvantages of R programming language

What is R programming language?

Language R programming is a language and environment for statistical and graphical computing that is very similar to the old S language. Of course, R should be considered a different version of S, which has many differences from it, but at the same time, it is similar to it in many ways. R uses an extensive library of statistical methods and graphing methods. In fact, it should be said that this language, as a well-known programming language, has found common use in a society governed by data mining, machine learning and data analysis. But among all the other languages, why should you be proficient in R?

In this programming language, there are many libraries or packages available that help you do all kinds of calculations. You can do it. As a language for data analysis, R is perfectly aligned with advances in machine learning and data visualization. R is becoming the ideal computing language for the programming community and is used in industries ranging from marketing to banking to pharmaceutical development. Simplifying the statistical analysis of large data sets, R offers several features, some of which include:

  • Clustering
  • Series Analysis Temporal
  • Linear and non-linear modeling
  • Easy interface compared to other languages
  • Very rich libraries and packages that are still expanding

R programming language, which has now become a very popular language in the community of programmers active in the field of statistical computing and data analysis, thanks to its open source and the benefit of a very powerful IDE, it makes the work much easier for programmers. has done. Also, this language has excellent compatibility with other languages such as C++, Java, and Python, which makes it possible to overcome any structural or computational weaknesses.

Can R be used easily? Did you learn and use it?

For data analysis, learning the R programming language is considered the best tool because it is known as the language of the computing world. But naturally, learning it will not be an easy task. This issue is especially difficult if you are a novice programmer because R requires background knowledge about various things. Machine learning, statistical modeling and different algorithms are sciences that learning them can be much more useful before learning a language than trying to go to this relatively complex language without any knowledge.

Although learning this language now It has become really easier before. This language can communicate with other programming languages such as Java, Python and C++ and even allows the user to perform operations and analysis on big data. This language currently benefits from the largest available set of libraries and packages necessary for statistical analysis. With more than 18,500 distributed packages (according to the latest statistics in 2022), this language has become extremely useful in analytical fields such as genetics, finance, medical imaging and social sciences, etc. So, if you're looking for a statistical technique, R will likely provide you with a package to implement it. There are times when you see that data visualization is not possible in other languages or requires writing long codes, but if you are familiar with R, you know that you only apply a few lines of code in it, but you get a much better result. Most of these advantages can be seen in the presentation of detailed and practical details and charts that are unique in terms of graphics and visual effects, and of course, providing comprehensive and complete information.

BingMag.com All about the R programming language

Use cases of R in different industries

Of course, the language of the program Writing R is not very complicated, but that doesn't mean it's easy to learn. You must first learn a series of basic concepts so that you can learn them in the best possible way. As a result, it is suggested that you first master the above-mentioned items and then start learning R or Python. It is not without reason that companies that perform very well in these fields, such as Microsoft, TechCrunch, Google, and Facebook, now use this programming language widely. Of course, Facebook mostly uses this language to analyze big data, but Google mostly uses this language to process the big data that its search engine produces every second and in the field of advertising and data analysis that exist in this sector. In Microsoft, R is used in many sectors such as finance and marketing, or applying machine learning to data.

In addition to these advantages, the R programming language has a very good performance in the field of parallel operations. Although this language was criticized for using only one processing core, but now, thanks to the changes made on it, the possibility of using packages and libraries and running calculations in parallel has been created, which allows users to perform operations in different cores of broadcast and do them at a much higher speed than before.

In general, we must say that this programming language is practical in this sense and it has become important among the programming community to check and Data analysis is a great tool. Modern analysis in machine learning, including clustering, time-series analysis, linear and non-linear modeling, etc., are among the activities that a programmer can perform thanks to the R programming language. do it simply and at a very high speed.

Should we use the R programming language?

Because these days artificial intelligence and machine learning are two very popular categories. and have become important in people's lives, learning them has become a necessity for those who work in these fields. Compared to other languages such as Python, which lack communication features, the R programming language benefits from a good balance between data analysis. Although learning it is not very easy, but considering that it provides many features and capabilities to users, spending time to learn it will be reasonable in the end. On the other hand, to learn this language, we need to get enough information in different fields, the most important of which is machine learning, which makes our work easier to do different projects.

BingMag.com All about the R programming language

A small list of famous R language packages

On the other hand, turning to this programming language by large and prominent companies in the world can be a motivating factor in itself. Good for those who are looking to learn a good programming language with a promising job market. Therefore, learning R language, considering that it requires a lot of skills before the learning process, eventually turns a user into an expert. However, in the matter of programming, practice is part of the work that has a great impact on becoming a professional. So just learning is not the end of the job.

Remember that data science like any other science needs a common language to communicate. Although there are many ways to communicate, there is a need for a tool that is comprehensive, complete and functional, all of which can be found in R.

Advantages and disadvantages of R language

Now that we are familiar with the use of R language, it is better to discuss its strengths and weaknesses so that you can learn it with more knowledge. Of course, keep in mind that each programming language has its own strengths and weaknesses. They cannot be considered perfect or full of problems. Each of them has advantages and disadvantages that must be dealt with according to your field of work. The R language is no exception to this rule. Among the advantages and disadvantages of the R programming language, the following can be mentioned:

Advantages

  • It is an open source language: This means that it is possible to work with it without the need for a license or a fee for everyone. Any data analysis is available. It is even possible to convert unstructured data to structured and regular data and examine them.
  • Supports a large number of functional libraries:With Programming, more than 10,000 packages are available in the CRAN repository, and their number is constantly increasing. Quality and precision are important to you, R language can do it for you in the best possible way. Diagrams can be drawn and customized in different types. It is possible to prepare comprehensive and detailed reports with this programming language. The user can combine the data with various charts and codes and display the result as a document with the highest level of detail.
  • Its compatibility with other languages is high:As in As mentioned above, this language has the possibility of compatibility with other languages such as Java, C++, Python and C. So you can connect with new database technologies like Hadoop and use them as a data source to work on large data sets.
  • It is independent of the operating system:
  • This programming language is operating system independent. It means that it is considered a multi-platform language and it can be used in any operating system.
  • It allows the implementation of statistical calculations:Statistics and statistical calculations are the reason that the language There is R. Therefore, he must have a lot to say in this regard. R is considered the international language of statistics and computing, and as a result it is superior to many other programming languages in this field.
  • It is a growing and evolving language:R although It's an old language, but thanks to being open source, it's constantly getting better. Every time we see that a new version of its libraries is updated with new features.

Disadvantages

  • Relatively complex language: We mentioned above that although R is no longer as complex as it used to be, learning it is not an easy task either. Those who do not have a programming background must first understand the basic concepts well before they can come to R, otherwise this language will be incomprehensible to them. Relatively low speed in executing operations: Compared to many other languages, the R language is noticeably slower in performing operations. Although it is possible to spread operations across cores for parallel processing, overall R is considered a slow language. Consider not mastering the packages available in R. Algorithms of this language are distributed in different packages that if a programmer does not have prior knowledge of them, it is difficult to implement the algorithms.

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