**Data Analysis with R, What is R language**: All those who start Data Science or try to start, face a very common problem. A question crosses in their mind that with which programming language they should start with. As they are going to invest their money and one of the most important thing i.e. time, so their question is genuine. As today there are so many languages, due to which we get confused that which is the best language. As each of the programming languages has their own pros and cons. So here we are going to brief you up with one of the most used and favorite language i.e. **R programming language** with which you should start working.

## What is R Programming language?

If we define R in a single line then it will not be enough. As R is a programming language, a data analysis software, it is an environment for statistical analysis and also an open source software project. So all this cannot be summed up in a line. **R language** was designed and came into existence 20 years ago to help academic statisticians and for all those with sophisticated programming skills to perform complex statistical data analysis and display results in any multitude of visual graphics.

Today R is being adopted by the enterprises for the big data analytics. R is a programming language and a software environment for graphics representations, statistical analysis, and reporting. R is freely available under the GNU General Public License.

- Data Scientists, analysts, statisticians, quants and all other make use of R for statistical analysis, predictive modeling and data visualization.
- In the R language, some of the main functions available are for data manipulation, charts which the data analyst could need and statistical model. The R is also famous as in this most cutting edge research can be done in statistics and predictive modeling.
- R is also an open source software project, this not only means that you can download and use the R language for free but its source code is also open for the modification and inspection to anyone whoever want to see the algorithms and methods. As like other open source, systems R also ha open interfaces, which means that it readily integrates with all the other systems and applications.

So R is unique as it provides a developer power to do 3 things data manipulation, data analysis, and data visualization in a single tool.

## Why R is important for data science professionals?

R is very important in the data science due to its versatility mainly in the field of statistics. Mostly R is used in the field of data science where a task requires special analysis. R is perfect when one needs to do analysis work. Below are some of the points that why it is important for data science.

- R is simple, well developed and one of the effective programming language that consists of loops, conditionals, recursive functions and input- output facilities.
- R provides operators for the calculations on vectors, matrices, lists and arrays.
- R has storage facilities and can provide effective data handling.
- R has the graphical facilities for the data analysis and display to either directly at the computer or printing.
- R provides a collection of tools for data analysis.

R is world’s most widely used programming language. It is the first choice of most of the data scientists and is also supported by a talented and vibrant community of the contributors.

### Importance of Learning R

R has more importance than any other language. So one should start with “R” language at first. Below we are listing some of the benefits/ **advantages of using R**.

- Ease of Coding

R provides a wide range of statistical and graphical techniques. The style of coding in language R is easy. Once you will start using it, you will get to know how easy it is. R community is mainly famous for its active and large contribution in the terms of its packages. As there are many standard functions that re written in R which makes it easier for its user to use it.

2. Data Manipulation

All those who work in data science can understand easily that most of the part in data science includes data manipulation. A data scientist usually spends most of his time to manipulate the data. By using R you can easily do it, as R includes a package that is called Dplyr Package. R consists of the best data management tool.

3. No Subscription Charges

As you are now aware that R is an open source language, so that is one of the benefits that you don’t need to pay any subscription charges. R is supported by the community developing it, that’s the reason it is open source and free. As with some of the languages, this is not the case, you have to pay subscription charges. This is also one of the reasons for its popularity.

4. R is a part of powerful companies

Nowdays, most of the powerful companies across all over the world are using R. The powerful as well as famous companies that are using R are Facebook, Microsoft, Uber, Trulia, Google, Ford and much more such companies. Facebook uses R for special tasks such as behavior analysis of its users. “R” is also used for weather forecasting by National Weather Science and Google is also among thousands of its users, mainly using it for tasks like e-commerce. Two most famous companies Facebook and Google have included R and these companies play an important role in the modern economy.

5. Most popular Language

According to various surveys done so far, it is found that R is one of the most popular **big data programming languages** and widely used language. According to a survey done by O’Reilly Media in 2014, it was found that a large number of the data scientists from all over the world are using language R and they have found it very helpful. The language is becoming famous day by day. Endless efforts have also been done to improve R’s user interface.

“R” was first released in 1990’s and at that time it was extremely popular, and its popularity is growing day by day with time. R contains many features which makes it more significant and powerful. R is also getting popular in various fields other than data science due to its features. In data science particularly, it is the best language to use and start with.