Python vs R: Which one is better?

Python is a versatile programming language with many tools, libraries, and frameworks. R is an open source statistical package used for data analysis. These are the two major competitors in the world of statistics software today that have both been around since 1990s. Who would you choose?

The “r vs python for data science” is a question that has been asked many times. There are many factors to consider when deciding which language is better. In this blog, I will discuss some of the factors you should consider before choosing between Python and R.

With the rising relevance of researching and mining data, statistical programming has grown more popular. With their enormous array of packages and tools, two prominent languages – Python and R – facilitate statistical programming.

We’ve briefly discussed each languages, outlined their benefits and drawbacks, and compared them in this page.

Python is a high-level, object-oriented programming language that is interpreted and interactive. It is an open-source, user-friendly programming language that finds important applications in AI, machine learning, big data, robotics, and GUI-based desktop software. It was first created in 1991.

It’s made to be very readable. It has a basic yet effective syntax. Its modules let you to do a variety of things, including object-oriented programming. It may be extended and communicates with OSI systems. It may also be customized with third-party extensions from the Python Package Index.

Python contains a large standard library of useful modules, as well as a collection of modules known as the Python “Standard Library,” which are included by default with the language. One of Python’s guiding ideas is that, rather than making things difficult to alter, users should be able to quickly expand and modify existing libraries and add new modules.

Python is a general-purpose coding language for beginners. Back-end development, software development, developing system scripts, data science, and statistical analysis are all possible with it.

Python for your operating system may be found here.

Python’s Advantages Python’s disadvantages
Reading, writing, and comprehension are all made easier. Isn’t the best platform for game and app development.
Dynamically typed and interpreted  
Free and open source software  
Debugging is made simpler with line-by-line code execution. Because it employs an interpreter, it is a little slower.
Has a large standard library built in.
Other programming languages, such as Java and C/C++, may be used with it.
It is platform agnostic; once the code is written, it may be executed on any platform.
Most databases are well-interfaced with this program.

Also see: Python vs. Java vs. C/C++: Key Differences and Advantages and Disadvantages.

R is a dynamic, procedural, object-oriented programming language that was first released in 1993. It comes highly recommended for doing statistical procedures, data science, and visualization. It’s compatible with UNIX, Linux, FreeBSD, Windows, and macOS.

Statistical interference, linear regression, machine learning techniques, time series, linear and non-linear modeling, clustering, and many more statistical and graphical approaches are available in R.

CRAN, a free and open-source repository for R libraries, has about 12,000 of them. Comprehensive R Archive Network is the acronym for the Comprehensive R Archive Network. These libraries may be used directly inside the R program by downloading them from CRAN. It’s also machine-independent, so it may be used on a variety of machines.

R for your operating system may be found here.

To get R software for your computer, go to

  • To get R, go to Download R.
  • Based on your location, choose a CRAN mirror.
  • Install the program on your computer.
Advantages Disadvantages
Excellent statistical analysis and computation Due of the difference syntax, it is difficult.
Libraries of a large size Graph quality may be harmed by redundant libraries.
Open-source Slow performance and poor memory management
Support for several platforms Low levels of security
Cleans, wrangles, and scrapes data from the internet.
Graphics with Impact
There is no need for a compiler.
It works nicely with other programs.
a vibrant community  

What’s the difference between Python 2 and Python 3?

While both Python and R have benefits and limitations, one should select Python or R depending on the final result desired. Scholars and academics are increasingly turning to R. Python, on the other hand, is preferred among programmers and developers. Because both have great statistical ability, there is no clear winner.

Parameter Python R
Type Language that has been translated Language that has been translated
Type of programming A language that is functional, object-oriented, structured, and aspect-oriented. A language that is both procedural and object-oriented.
IDE Spyder, Ipython Notebook RStudio
Uses For development and deployment, a general-purpose language is used. The use of statistical terminology and the interpretation of graphs
It is ideal for Learning at a deeper level Visualization of data
Maintenance Language that is both robust and simple to maintain It needs more upkeep.
Packages There is just one bundle for a single job. For a same job, there are several packages.
Statistical software Weaker Stronger
Speed R is faster. Python is slower.
User-friendliness It’s easier to create models from the ground up. It’s more convenient to utilize an existing library.
Size of the database a big size a big size

Also see: C vs. C++: What’s the Difference?


An engineering student, a creative geek, a TT player, and a voracious reader.

The “python vs r reddit” is a question that has been asked many times before. The answer to this question, however, is not as clear cut as one might think.

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Frequently Asked Questions

Whats better R or Python?

A: R is better than Python, but both are very good at what they do.

Is R more efficient than Python?


Is R or Python more popular?

A: R is a programming language, Python is an interpretive high-level programming language.

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