The letter R defines as a language “of the environment of graphical representation, statistical representation, statistical computing and designing”
Ross Ihaka and Robert Gentlemen at the University of Auckland in New Zealand in the 1990s they invented a language for their student for statistical purposes called R , the letter R is the initial of both developer’s names, and R is the implementation of S programming language.
R for Data Science
As Data Science is used to represent the data in statistical and graphical form , R is one of the best language/tool to implement/solve the problems related to Data Science , like
- Linear and non-linear modeling :- With the help of R , you can work with both linear and non-linear data , R can help you on both with linear or non-linear equations.
- Time-series analysis :- Time series is a series of data that deals with the time series of data , or trending analysis . The meaning of data is in series of particular time period or intervals.
- Clustering :- Cluster analysis or clustering is the thing of grouping a set of data in such a way that the object in the same cluster.
Why do we use R for data science?
R is one of the most powerful tools used by the world’s leading companies to implement or analyze the data, R language is easy to understand and can easily to exact as per user. R can be used in different fields like
- Finance
- Genetics
- Medical Images
- Social Science
- High-performance computing
R is one of the most powerful languages which is used by data scientists for decades, we can use R language with the help of R-studio, and R can be used in open-source software projects. A data scientist uses R language widely adopted in the field of graphical and statistical reprentation of data.
