Why Choose R For Data Science

Why Choose R for Data Science

With an exponential increase of data in every organization has led to the rise in demand of proficient data analysts and scientists with advanced knowledge of analytical tools and some programming language which can help to generate insights of data. R programming has an important role in data science field. Here it is necessary to mention that R is not as popular as other programming languages like Java and Python, but still there are number of developers largely prefer to use R programming language for development of their statistical and data analytical software. R is also an open source programming language come with an excellent IDE (Integrated Development Environment). Primary function of R programming is to perform statistical computing, data analysis and data mining. R is widely used in many industries to carry out analytical outcomes from structured & unstructured datasets that makes it most prominent among data analysts and data scientists.

R programming is a must have skill any data analyst and scientist and there are many reasons to learn skill sets of R and we are going to list down major ones:

  1. Open Source Language:

R is an open source programming language that means anyone can work with R without worry to purchase license or to paying any fee.

  1. Data Wrangling Support:

R programming langauge provides a perfect support to perform data wrangling task by offering different packages like dplyr and readr which are capable to convert large messy datasets into a well structured form.

  1. Graph and Plotting Features:

R has popular libraries like ggplot2 and plotly that administers the use of visually appealing graphs & plot charts apart from other programming language.

  1. Compatibility:

R is highly compatible i.e. most of its functions and packages are present in R itself which can be paired with many other programming languages like C, C++, Java and Python. Database management systems such as Hadoop and various others can easily be integrated within it.

  1. Platform Compatibility:

R delivers the reliable data driven outputs while supporting a wide variety of operating systems with any software and hardware configuration.

 

  1. Comprehensive Statistical Computing:

R programming language is prominently known for developing statistical computing tasks as well as for software development which makes it more dominant programming skill in data experts. It can be used for data analytic tasks, making data relevant reports & to develop interactive web apps also.

  1. Continuous Growth:

R is constantly growing programming language that provides state of the technological features and provides regular updates whenever any new feature is added.

  1. Use Cases Across Various Industries:

In present scenario, every big industry is using R for many reasons. Few of those industry domains are financial & pharmaceutical firms, social media channels and E-commerce & telecom companies.

Financial firms are using R for risk assessment overview & upcoming market predictions whereas online shopping & telecom companies taking benefits from R to identify a group of prospective customers targeted advertisements. Another useful task that R can perform to analyze customer sentiment and their feedbacks.

Social media companies are using it for improving the customer feedback on posts and blogs & to track out their behaviour analysis.

 

Conclusion:

In this article we have learned the various reasons for choosing R programming language if someone wants to start his or her career as data engineer apart from Java and Python.

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