Difference between R Programming and Python Programming
Below are some major differences between R and Python:
Feature | R | Python |
---|---|---|
Introduction | R is a language and environment for statistical programming which includes statistical computing and graphics. | Python is a general-purpose programming language for data analysis and scientific computing |
Objective | It has many features which are useful for statistical analysis and representation. | It can be used to develop GUI applications and web applications as well as with embedded systems |
Workability | It has many easy-to-use packages for performing tasks | It can easily perform matrix computation as well as optimization |
Integrated development environment | Various popular R IDEs are Rstudio, RKward, R commander, etc. | Various popular Python IDEs are Spyder, Eclipse+Pydev, Atom, etc. |
Libraries and packages | There are many packages and libraries like ggplot2, caret, etc. | Some essential packages and libraries are Pandas, Numpy, Scipy, etc. |
Scope | It is mainly used for complex data analysis in data science. | It takes a more streamlined approach for data science projects. |
R vs Python
R Programming Language and Python are both used extensively for Data Science. Both are very useful and open-source languages as well. For data analysis, statistical computing, and machine learning Both languages are strong tools with sizable communities and huge libraries for data science jobs. A theoretical comparison between R and Python is provided below:
In this article, we will cover the following topics:
- R Programming Language
- Python Programming Language
- Difference between R Programming and Python Programming
- Ecosystem in R Programming and Python Programming
- Advantages and disadvantages in R Programming and Python Programming
- R and Python usages in Data Science
- Example in R and Python