There are too many programming languages that are used on a regular basis by developers. But these days the popularity of R programming and Python has increased up to a great extent. It helps a lot in artificial intelligence in machine learning as well as in data science. Many students these days are using R and Python for their projects as well. In this blog, we will discuss 20 differences between R and Python.

What is R programming?

What is R programming
What is R programming?

R is a programming language. It is a free software environment for doing statistical computing and graphics. The R language is mainly used among statisticians and data miners for developing statistical software and data analysis.

What is Python programming?

What is python programming
What is Python programming?

Python is an open-source programming language. It is an interpreted, high-level, general-purpose programming language.

Why R and Python?

R and Python are both open-source programming languages with a large community. On a regular basis new libraries or tools are added continuously to their respective catalog. R is mainly used for statistical analysis while Python provides a more general approach to data science.

Differences between R and Python Programming 

1.    DefinitionR is a programming language that is mainly used for statistical computing and graphical calculation.Python is an interpreter based and high level and programming language that consists of dynamic semantics.
2.    ScopeMainly used for statistical ProgrammingUsed for web development applications and analysis of the data
3.    IntegrationIt is integrated with locally run programsIt is an integrated web development apps.
4.    IDERStudio, RGUISpyder, Ipython
5.    Package distribution


6.    SuitabilityPeople with no experience can learn thisNew learners to experienced ones
7.    PackagesIt has 100 of packagesIt has a few packages
8.    ApproachComplex data analysisStreamlined approach
9.    Analytic ModellingHigh level is achieved hereLow to medium only
10. Tool advancementsLow advancement in RMedium level advancement in Python
11.  DescriptionIt acts as a golden child of data scienceIt acts as a king of data science programs
12. RankingR is at 6th placePython is at first rank
13. Job OpportunityR provides less job opportunitiesPython develops more job opportunities to its developers
14. UsersNumber of users are lessNumbers of users are more
15. Learning curveIt is difficult to learn at the beginningIt is easier and smooth to learn
16. SalarySalary of R programmer is less than Python developersSalary package is comparatively high
17. DisadvantagesIt has a slow learning curveIt has fewer libraries as compared to R
18. LibrariesIt has more librariesIt has fewer libraries
19. Primary UsersScholar and R&DProgrammers and developers
20. Good forIt is good for analyses and exploring data setsIt is better for data manipulation and repeated tasks.


Many Startups and MNCs are dependent on these technologies in order to expand and leave a mark in the industry. Many students are learning these technologies to become more skillful. Those who want to enhance their career in machine learning and data science must learn R and Python. It offers a number of libraries to work on. Both languages are highly demand. In this blog, we have discussed 20 differences between R and Python. If you are having any doubt, feel free to ask me in the comment box.


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