data science Training in Pune

Before delving deep into how to use R in the data science process, let’s understand the terms- R and data science individually. R is a programming language created by Ross Ihaka and Robert Gentleman, the University of Auckland faculty members. It is a statistical programming language that data scientists and business leaders widely use to interpret data. Now let’s understand what is data science.
Data science is what one can call complex Math- a multifaceted field that uses different scientific and mathematical tools, processes, methods, and systems to collect data which is then analysed with the help of programming languages like R, Python, C, Java, and others.

Various programming languages are compatible with carrying out the data science process, but R makes evaluating and collecting Data thrilling and unique. R is an advanced language that performs various complex statistical computations and calculations. Therefore, it is widely used by data scientists and business leaders in multiple fields, from academics to business.
Moreover, R interprets the data in a graphical form, making it easy to interpret and understand. In addition, R has different options for advanced data analytical processes like machine learning, algorithm, etc. Lastly, performing various data science processes is easy with R because it excellently works for data wrangling, data visualization, statistical calculations without vectors, and web applications, among others making it easy to collect and analyze huge amounts of data in a jiffy.
Now that we know that R is the mightiest computer language for data science, let’s delve deep into R programming language’s working mechanism, fundamentals, and features.

1. Open-source
R in data science is free software that is accessible to everyone. Furthermore, the programming language is adaptable, making it easy to integrate with different applications and processes. Despite being open-source software, the programming language exudes quality and is usable and versatile.
2. Powerful graphics
This is one of the attractive features of R programming. Many data scientists use R while analyzing data because it has static graphics that produce good-quality data visualizations. Moreover, the programming language has a comprehensive library that provides interactive graphics and makes data visualization and representation easy to analyze. From elaborative and interactive flow diagrams to bar graphs, R has everything that makes data analysis enigmatic and easy.
3. Widely used
R fosters a community of its own. The programming language is widely used by data scientists and business leaders across the globe because it is an open-source computer system that evokes a sense of community among its users.
4. Performs complex statistical calculations
R’s wide popularity is because of its ability to perform simple and complex mathematical and statistical calculations. It is also used for analyzing data in many industries.
5. Compatibility
R is compatible with computer programs like C, C++, Java, Python, etc. Its functions can be easily integrated into different computer programs.
These features and more make R a favourite choice of many data scientists. Interestingly, web applications like Twitter, Google analytics, BBC, others use R in data science. They use it to collect data and create clear data visualizations or graphs to draw inferences and implement their business conclusions. If you are a data scientist wondering how to procure R for data analysis, proceed to the next section wherein we have explained how to install the R program below.