Why is R fit for Data Sciences

Over years, whenever someone talks about learning data science analysis, the first question that comes up, “which programming language to opt for”. Well, it is not only about the programming platform but systems are well. With the advancement of technology, the programming languages, software systems and a wide range of tools have made it even more confusing to select any one. However, the fact remains constant that R is actually the future of the word of data sciences.

It might be confusing on where to start, after all, no one wants to waste their time in completing a task only to come out empty handed. If you are aiming for an effective tool then you need to make sure that you are selecting a right tool and also to learn how to use too. This will help you to set your business in the right direction. There are many things that will make you drop dead to stick to R.

There is a major chance that you are stuck with questions such as the future of R, the revenue, the benefits, and even why is it different than any other language. Well, here is the answer to all your worries. There are so many reasons for R to be the topmost and in-demand skill:

Cross platform compatibility

R is the most wanted software because it allows you to run on any of the operating systems. There are not many programming languages that allow you to do so since they depend on specific hardware or software. However, this is not the case with R since it can run smoothly on any type of Operating system that can be Mac, Linux, or even Windows. This is omitted from the problem of you and your client working on the different operating system.

Open Source

It is an open source and free software with plug and plays functions. You can simply get R installed and have your own working fun with it without worrying about the small things. Well, there is more than that, you can modify or add your own innovation or code to the existing one to improve it on your end. It is a language that allows you to do as per your demands without any restrictions since it is issued under the GPU license.

Community

One reason why people go for R is that it has a vast community that gives you a vast knowledge base. The data is so vast in R that will make you reach out to anything if you are stuck at a single point. You can seek anyone’s help at any point from a person who has already dealt with the similar issue. It will allow you to share your ideas with others, compute the Data science and even work on the projects.

Domains

R programming is the one that is used to by many of the many financial domains that helps them to build off the econometric models and also to analyze the fraudulent transactions. Another of the domains that widely depend on the R is telecom sectors for the personalized advertising, churn management and subscriber profiling. This programming language is also used in the computational biology that allows people to perform many of the genomic analysis.

Visualization

If you are using the R then you can create stunning and amazing visualizations with the help of packages such as plotly, ggvis and ggplot2. You will be able to develop the print-quality graphs that will allow you to publish them in any of the national and international magazines. It is used by the pharmaceuticals due to the high and standard quality graphics that help in experimental procedures.

Wide range of libraries

There are more than 10,000 packages and also more than lakh inbuilt functions that can help you to cater the different requirement of your client. It is possible for you to perform a number of functions with the help of these packages such as Data Visualization, Data Manipulation, Statistical Modelling, Machine Learning, Imputation and the list goes on. R is springing its way up to the top with the help of these number of packages that can help you in a lot of ways. On top of that, R is an open source software that allows you to contribute to it by adding any of your own packages.

Components

There is no doubt that the top companies like Facebook, Ford, Google and even Twitter are using R. Facebook is a huge fan of its behavioral analysis that helps them in the process of profile pictures and status updates. For Twitter, it is a great way for the semantic clustering and data visualizations. Google depends on R for forecasting economics and even the effectiveness of the advertisement. The vehicle design improves is widely popular among the workers of Ford.

Interactive applications

The topmost problem for the data scientist was that there were no software that can help them to build an interactive application through which they can easily analyze data. When the shiny is there to help you out. It is a package of R that can help you to create attractive and interactive applications and webpages with the impressive dashboard from R console. On top of that, it also allows you to create a shiny web app and then allow cloud hosting such as AWS. It can be extremely helpful for the data science.

Data science

It is a statistical software that will help you to create statistical data. You can perform a number of things with the help of this language such as measuring the central tendency and also building up the complex statistical models. This go-to language can be extremely helpful for you for many of the analysis. There the machine learning models that can be a bit complex can be build up with the help of R functions. The models that are built are Poisson Regression, Gaussian Process Regression and Random Forest.

R is many things!

• R is the best software for data analysis. It is so simple to make sense of data by statisticians, data scientists, and even analysts. You can use R for data visualization, statistical analysis and predictive modeling.
• R is best for statistical analysis environment. These types of standards can be implemented in an easy way with the help of predictive modeling and cutting-edge research.
• It is a programming language that depends on the concepts of Object Orientation. R offers operators, objects and functions giving a chance for the user to model, explore and visualize all the data.

R offers a number of features that a data scientist can take advantage of such as:

• Interfaces easily with extensibility with other languages
• Analysis as per time series
• Sizable sharing of codes that are in the repository package
• Non-linear and linear modeling
• Clustering of data

These are just a few of the reasons that makes R best for Data Science. Another thing is that R is a free software with a lot of intellectual and financial properties that help developers to maintain a project. If you are considering the career in this field then it is the best way to opt for. Just be more familiar with R to get a better hang on it.

If your organization needs an implementation for a big data analysis program, get in touch.