In 1995, R programming was released and since then, it has turned out to be an absolute global phenomenon. Such is the demand for R programming that it has become an important facet in data science. The volume of Google search for data science training in Mumbai and data science training in Pune have considerably gone up as students are taking a keen interest in the subject.
R is primarily known to be a language which is user-friendly and helps a user to understand and perform statistical analysis, data analysis, and graphics modules. Let us dwell more into the importance of R programming by taking note of its features.
Free and easy to use – R is a simple and efficient programming language which runs on all OS platforms. It is easily available to anyone enthusiastic enough to learn R.
Complete analysis kit – One of the main unique selling points of R is how comprehensively analysis can be done. R has a range of tools for data and statistical analysis.
Used by major players – Facebook. Twitter. Google. Microsoft. Uber. New York Times. And this is just the upper layer of the top tier companies that use R programming.
Facebook – For behavior analysis related to status updates and profile pictures.
Google – For advertising effectiveness and economic forecasting.
Twitter – For data visualization and semantic clustering.
Microsoft – Acquired Revolution R company and use it for a variety of purposes.
New York Times – For data visualization
Use of data charts – The best and the easiest way to represent data is by using charts. Charts give a fair idea about the progress or decline of a company or individual. R programming aids data visualization; whether it is bar graphs, line graphs, pie chart or scatter plot. The chart and graphs offered by R programming go a long way in influencing key decisions.
R packages – R programming has a total of 24 packages, all diverse in their own way. For instance, ‘tidyr’ makes it easy to “tidy” your data. Having a clean data helps in making charts and visualizing and thus helps in making models using the same data.
Conclusion
In all fairness, you can see how important R programming is in data science. Despite the use of python, R programming still remains as the number one statistical language. Big companies like Facebook and Google still use R to collect valuable data, visualize and create models to help revenue and business. Data science is on the up and if there is a time to forge a career in it, now is the time.