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Last Updated: Mar 27, 2024
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Introduction

R is a statistical computing and graphics programming language. It is used for statistical software development and data analysis by data miners, statisticians and bioinformaticians.

Python is a general-purpose, high-level programming language. Python is garbage-collected and dynamically-typed. It supports a wide range of programming paradigms, including structured (especially procedural), object-oriented, and functional programming.

So now, in this article, we will discuss R Programming Language vs Python programming language.

r vs python

 

Key Differences (R language vs Python)

  • R is mostly used for statistical analysis, but Python takes a broader approach to data science.
     
  • R's major goal is data analysis and statistics, whereas Python's primary goal is deployment and production.
     
  • R users are largely academics and R&D professionals, whereas Python users are mostly programmers and developers.
     
  • R allows you to use existing libraries, whereas Python allows you to create new models from scratch.
     
  • R is tough to learn at first, whereas Python is linear and easy to master.
     
  • R is built to run locally, whereas Python is well-integrated with apps.

Above are some key points of R language vs Python.

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What is R

R

R is a programming language built on the S-PLUS programming language and enhanced with lexical scoping semantics. Major codes in S-PLUS are not changed and can still be seen being executed in R. R also offers an open-source software environment that is extremely beneficial for statistical and graphical reasons. It is mostly utilized by statisticians and data miners. Notably, the R Foundation for Statistical Computing maintains the R language.

R has evolved significantly since the release of S-PLUS, the commercial version of S. While working at Bell Labs, John Chambers invented R's predecessor, S in 1976. R was first announced in 1995, with CRAN, or the Comprehensive R Archive Network, following shortly after in 1997. By the year 2000, the official beta version had been pronounced stable. R is one of the most used programming languages in the world as of 2021.

R's approved software environments are GNU packages written mostly in R, Fortran, and C. It is somewhat self-hosting in nature. R encourages object-oriented programming, which has high statistical computing requirements, as well as the use of Python, C++, or Fortran codes for manipulation and computationally expensive tasks.

Advantages of R

  • Amazing graphs and interactive graphical representations are created using R programming.
     
  • Massive data analysis catalogs are available.
     
  • Shiny is used to create amazing web applications directly from R.
     
  • R includes a Github interface.
     
  • R supports RMarkdown, which enables a variety of dynamic and static output formats, including HTML, MS Word, and PDF.
     
  • R can be used for descriptive and summary statistics such as central tendency, kurtosis detection, variability assessment, and skewness.
     
  • R supports both discrete and continuous probability distributions. For example, the ppois() function can be used to allow Poisson distribution, while the dbinom() function can be used to draw binomial distribution.

Disadvantages of R

  • R requires more memory since all items are stored in physical memory. As the program accumulates more data, the process slows down.
     
  • R lacks fundamental security, making it difficult to incorporate into web applications.
     
  • Unlike Python, R is a complex language that is tough to learn for a beginner.
     
  • R is a slow language to process. Generating output takes longer time than other programming languages.
     
  • Data handling in R is time-consuming since it requires all data to be in one location. It is unsuitable for Big Data. It does, however, include an integration that makes handling slightly easier.

What is Python

python

Python is an interpreted high-level programming language, which implies that it may be run without being compiled into machine language. Python is extremely adaptable and versatile, and it can be used for both large-scale projects and small-scale operations.

It employs an object-oriented paradigm as well as a functional and structural approach that encourages logical, clean, and legible code. It is supported by a large standard library, which increases Python's viability. Python is the successor to the ABC programming language, and it was first developed in the late 1980s before being released in 1991 as Python 0.9.0. Python 2.0, a newer and improved version, was released in 2000, with Python 3.0, the finest version to date, was released in 2008.

Python 3 gained a lot of attention and popularity after its release. It soon became one of the world's most popular programming languages. Python gives developers the ability to adopt specific methodologies or combine different programming paradigms, making it a multi-paradigm language. It strongly encourages and supports object-oriented and structured programming while also encouraging functional and aspect-oriented programming.

Advantages of Python

  • Python is amazing with production and deployments.
     
  • Outstanding mathematical computations.
     
  • Python offers code readability.
     
  • Aids in the development of prediction models and exceedingly sophisticated computer models.
     
  • Allows machine learning techniques to be implemented and advances artificial intelligence.
     
  • Aids in data sharing via notebooks.
     
  • Very quick and allows for quick execution.

Disadvantages of Python

  • Python is an interpreted language, which means it runs slower than other programming languages.
     
  • Python is incompatible with Android and iOS environments. In such an environment, developers claim it is a weak language. It can, however, be used with additional effort.
     
  • Python uses a substantial amount of RAM. When more objects must be accessed, the process becomes slower.
     
  • Python's database access layers are less developed than those of Java Database Connectivity (JDBC) and Open Database Connectivity (ODBC), making it a less popular database connectivity.
     
  • Because of Python's Global Interpreter Lock (GIL), threading or the flow of many functions at the same time is a disadvantage.

R language vs Python

Features R Python
Introduction R is a statistical programming language and environment that integrates statistical computing and graphics. It is used for general purpose programming, scientific computing and data analysis.
Objective It is extensively used for statistical analysis and representation. It can be used in deployment and production. It is used in developing GUI and web applications.
Primary Users It is mainly used by Scholars and people who are inclined to research and development. It is mainly used by programmers and developers.
Learning Curve It is a bit difficult to learn for those who are new in programming. It is easy to learn even for beginners.
Workability It offers several simple packages for carrying out tasks. It is capable of performing matrix calculations as well as optimization.
Packages and Libraries Ggplot2, caret, stringr, and shiny are some of the essential libraries. Pandas, matplotlib, numpy, sklearn, and scipy are some of the essential libraries.
Scope It is mostly used in data science for sophisticated data analysis. It is mostly used in data science for simple data analysis.
Intergation It runs locally It runs with a well-integrated app.
IDE Rstudio Ipython, Notebook, Spyder

Also see, How to Check Python Version in CMD

Which one to choose: R language vs Python?

When it comes to the use of Python and R, this is arguable. Each of these languages has benefits and downsides. Python is widely used for numerous purposes, although R is also in use. Python is utilized for a wide range of features, but R is mostly used for statistics. It is up to the user to select the language based on their needs.

Frequently Asked Questions

What is Python language used for?

Python is a computer programming language that is extensively used to create websites and applications, automate operations, and analyze data.

What language is Python?

Python is an object-oriented, interactive, interpreted programming language.

Who uses Python?

Python is used by IBM, Intel, Pixar, NASA, Netflix, JP Morgan Chase, Facebook, Spotify, and many more large corporations.

Is R the same as Python?

Python and R are high-level, open-source programming languages that are widely used in data science and statistics. However, R is best suited for classical statistical analysis, whereas Python is best suited for traditional data science applications.

What type of language is R programming?

R is a free and open-source programming language designed for statistical research and data visualization.

Conclusion

In this article, we learned about the major differences between R language vs Python. Later, we looked into each of the programming languages individually. Lastly, we learned which of the two is better according to conditions. We hope this article on R language vs Python was helpful. For more such articles like r language vs python, you can visit the following sites:


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Topics covered
1.
Introduction
2.
Key Differences (R language vs Python)
3.
What is R
4.
Advantages of R
5.
Disadvantages of R
6.
What is Python
7.
Advantages of Python
8.
Disadvantages of Python
9.
R language vs Python
10.
Which one to choose: R language vs Python?
11.
Frequently Asked Questions
11.1.
What is Python language used for?
11.2.
What language is Python?
11.3.
Who uses Python?
11.4.
Is R the same as Python?
11.5.
What type of language is R programming?
12.
Conclusion