Hey, guys! While learning R language, have you ever wondered why we need to learn and use R? If yes, let’s follow our article. We will help you answer your question.
Firstly, we need to understand the definition of R.
What is R?
R is a free software computer language. Ross Ihaka and Robert Gentleman created it in 1993. R has an extensive library of statistical and graphical techniques. It includes statistical inference, time series, linear regression, and machine learning techniques. Most R libraries are written in R. However, C, C++, and Fortran codes are favored for complex computational tasks.
R is not only trusted by academic institutions; many major corporations, such as Uber, Google, Airbnb, Facebook, and others, also use it. Why are so many big corporations using R? Let’s follow the next part to find the question.
Reasons why we need R
Below are some reasons why we should add R to our skillset:
- Firstly, R is an open-source language, so you can freely download, use, update or change the code and add your innovations. This helps businesses save money while making simple improvements, which is helpful for a statistical programming language.
- Linux, Mac OS X, and Windows all support R. Additionally, and it can import data from programs like Microsoft Access, SQLite, MySQL, Oracle, and Microsoft Excel. R can manage huge, complex data collections as a result. R can be utilized on high-performance computer clusters and is the best language for extensive, resource-intensive simulations.
- R may be used to implement the best machine-learning algorithms. High-end machine learning techniques can be created using packages like Keras and TensorFlow. The best algorithm for the Kaggle competition, Xgboost, is also available in R as a package.
- R offers more than 10,000 packages and tens of thousands of built-in features to meet various purposes. You may experiment with packages for data visualization, data manipulation, machine learning, imputed data, statistical modeling, and many others. R, therefore, produces a package to assist you, whatever your demand may be. You also can build your package because R is open source.
- R offers programs like ggplot2, ggvis, and plotly, making it easy to produce beautiful visualizations. These tools assist in producing graphs of print quality that can be included in any international magazine.
- R can converse in the other language. R supports calls to Python, Java, and C++. R has access to the large data universe as well. R may be linked to various databases, including Spark and Hadoop.
In brief, R is a fantastic tool for data exploration and analysis. R is used for complex analysis, including clustering, correlation, and data reduction. Implementing machine learning will only produce beneficial results with solid feature engineering and a model, which is the essential step. If you want to know more about R, let’s read these tutorials for R. They are helpful for you.
After reading here, have you found that R is a language worth learning and using? It is a language with many benefits, so don’t hesitate to learn it right now. Hope you study well!