R is becoming on of the most popular language in the world . Due to increasing the need of big data. R comes into the popularity index among students. Basically R is used for statistical computations, data analysis and Graphical representation of data. R is facing a huge competition from Python. Let’s talk about the reasons why R is that much popular:-

### Data Wrangling

Data wrangling is the process to structure the unstructured data for further analysis. This process takes a lot of time in data science. The data is collected from various sources. Therefore each source has its own way to present the data.So it becoming hard to manipulate the data and it takes lots of time. But with the use of R language the data wrangling process become easier. Here the the reason why it is easy to manipulate and wrangle data using. The following tools in R make this process easy:-

- Deplyr
- data.table Package
- readr Package

### Data Visualization

Data visualization is the process to visualize the data in graphical form. This helps in analyzing the data through angle that are not clear in unorganized data. R comes with the large number of tools for data visualization, analysis, and representation. The standard plotting packages of R is ggplot2 and ggedit. While ggplot2 is use for data visualization. On the other hand ggedit helps data scientist in bridge the gap between making a plot and getting all of those pesky plot aesthetics precisely correct.

### Specificity

R is not common as other programming languages. R is especially designed for statistical and data reconfiguration. The library of R is especially designed to make data analysis easier, more detailed and approachable. R libraries enable each and every new statistical methods. Therefore R becomes the perfect choice for data analysis and projection.The best part of R language is that it holds a large community where each and every aspirant help each other to solve complex problem with R language

### Machine Learning

Data science is all about the prediction. That is why the data scientist need to build up an algorithm that can make prediction. For this R provides large numbers of tools to developers to train and evaluate an algorithm and predict future events. In this way R is contributing in machine learning to make it more easier and approachable. R machine learnign packages include these tools.

- MICE
- rpart & PARTY
- CARET
- randomFOREST

### Availability

R is an open source programming language. Therefore it is free to use and implement in the data science project. It is a better and cheaper option to develop large projects. There are lots of free resources available online for R languages. any beginner can learn R programming language with the help of community members of R. Even an company can hire the R developer through the community that makes it cost effective data science programming language.

### Conclusion:

R is easy to learn and you can explore huge opportunity in this language. If you are looking to start your career in data science then this is a solid language to start with. This is beneficial for both the company and for the developer. If you are already doing data science course then you can R programming assignment help to score higher grade.

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