Want to dive into the world of data science? If so, the R language, commonly referred to as the R language, is something you need to learn.
Yes, with little knowledge, it turns out that programming languages are not only used by programmers or developers. Now, there is an actual R language that is often implemented for data processing and analysis.
Not only that but this programming language can also be used for data visualization, you know. In fact, the visualization itself is considered not arbitrary alias quality.
How? Intrigued by R language sundries? Come on, see the description below!
What is R?
What is R? the R language is a programming language, aka programming language. It is used for statistical computing and graphics. Glints have mentioned this above.
Geeks for Geeks said this language is a development of the S. R language itself, designed by two figures from the University of Auckland, Ross Ihaka and Robert Gentleman.
Well, the world in which it is used, namely data, is proliferating. Apparently, R himself also experienced the same thing.
Quoting TechRepublic, as of August 2020, it occupies position 8 in the top 10 programming languages list. This language scoring system is owned by the programming community, TIOBE.
He’s not just popular, you know. Quoting Guru99, the R language can be used to implement machine learning algorithms. Career Karma said R language is also data science-friendly. It can also be used to process big data.
What’s more, he can also communicate in other languages. Other languages are, for example, Python, Java, or C++.
There are 5 main data types present in this language. The data types are:
- list
- vector
- arrays
- matrix
- data frames
- table
- factor
Features in R Language
R language comes with several interesting features that will help many people, not only professionals but also ordinary people. The following are the features presented by the R language:
1. Features of R Statistics:
Basic Statistics: The most common statistical terms are mean, mode, and median. These are known as “Measures of Central Tendency.” So, we can measure central tendency using the R language very quickly.
Static Graphic: R language has several facilities for creating and developing attractive static graphics. R contains functionality for many plots, including graphical maps, mosaic stories, biplots, and many more.
Probability Distribution: Probability distribution plays a vital role in statistics, and by using R, we can efficiently deal with different types of probability distributions like Binomial Distribution, Normal Distribution, Chi-square Distribution, and others.
Data Analysis: It provides a significant, coherent, and integrated set of tools to perform data analysis.
2. R Programming Features:
R Package: One of the main features of R is the availability of a vast library. R has CRAN (Comprehensive R Archive Network), a repository capable of holding more than 10,000 packages.
Distributed Computing: Distributed computing is a model in which system software components are shared among multiple computers to increase efficiency and performance. Two new packages, DDR and multiplier, used for distributed programming were released in November 2015.
R’s advantages
Who says good quality stuff has to be expensive? R is one of those programming languages that proves that to be wrong.
The R language offers sophisticated data analysis capabilities. In fact, said Tech Target, it is free.
What’s more, this language is quite “mature.” It has many users, so many communities continue to develop it.
The data visualization feature is also not arbitrary. Quoting Fast Company, this feature is relatively high-quality and can produce beautiful graphics.
Launching Career Karma, this language is also really used. It is not just the language of data analysis activists because of a hobby.
Technology giants such as Facebook, Google, and Microsoft use the R language. Apart from that, there are also other large companies such as Bing, Merck, TechCrunch, to Mozilla.
R deficiency
Indeed, Glints has made it clear that the R language is relatively easy to learn. However, JournalDev says this is not a language for beginners.
Because the command-line display of this language is confusing. So, as a solution, you can use an integrated development environment like RStudio.
Data in R is also stored in physical memory. This can be one of the drawbacks.
What if you have to work with a vast amount of data? You might need more memory.
R already integrates with Hadoop, a framework for extensive data.
R code reading alias execution also takes a long time. If you really want to speed things up, you have to be prepared to optimize your code.
What Does R Used For?
Initially created for the purposes of analysis in the field of statistics only. In fact, until now, it is still widely used by the majority of statisticians. For example, when creating a complex statistical model.
Generally applied in the academic field. Therefore, for those who desire to work in this field, it is mandatory to understand this programming. The goal is to make work easier.
Data Science Application
Many large companies require data scientist applicants to master the language. In practice, programming is applied to more than just technology companies.
Banks, consulting firms, and various financial and academic institutions also use it. The reason is that there are many packages that you can choose to support data science.
Examples include data.table, plyr and dplyr. All packages in the R programming language make it easy to manipulate data. Meanwhile, for data visualization purposes, you can use containers such as lattice, ggvis, or ggplot2.
All packages are easy to operate by the user. Thus, it will be easier for you to adapt when learning about the programming language.
Thus, it can produce exciting visualizations. For example, when you need a graph, you can use ggplot2. Then, if you want to display it in a web browser, use ggvis.
Its growth is among the fastest in the world. This is possible because of the support from large communities such as Stack Overflow. If users experience problems, they can immediately take advantage of the community.
R Implementation
R is one of the most popular languages because it is widely used by large companies. Examples include Facebook, ORBITZ, Airbnb, Microsoft, IBM, Google, Uber, and others.
Facebook uses it to analyze user behavior. In contrast to Google, which is more focused on evaluating the effectiveness of advertisements, there are many other examples.
In general, these companies use it when conducting cross-selling analysis. Later, the results of this analysis can be used to provide the best product offers according to consumer routines when shopping.
For example, building machine learning by data scientists then processing large amounts of data. In addition, it presents the statistical model needed by the company.
The R programming language can also be applied for various purposes. Its existence is vital because it has a continuously updated package according to technological developments.
There are more than 12 thousand packages, and they will continue to be added in the future. One of the advantages is that it can be applied to the web or robot. Plus the features offered are also many.
You can take advantage of various statistical and syntax functions. All available tools help you perform statistical tests and different other data analyses. Then, there is the GUI or Graphic User Interface.
One example is RStudio which is user-friendly. The components in it include the console, graphical output, and others. In addition, there are also several tools to support data processing activities.
Having RStudio helps you when you create reports automatically in various formats, both pdf, and word. This can happen because there are many package options available.