R and Python are two of the most popular programming languages when it comes to data science. They are both open source, free to use, and have a lot of similarities. That said, both languages have their differences as well. While R has been in the game for quite some time, Python is newer. This blog will discuss some similarities and differences between R vs Python.
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What is R?
R is a programming language. The use of this language for statistical analysis. It’s beneficial for the complex analysis of datasets. However, it is also regularly used for modeling, predictive analytics, and data visualization. While it can be difficult to learn, it’s useful for professionals looking to get ahead in the market.
As the market continues to grow, the demand for R experts will also likely grow. However, learning R is a good idea if you think you have what it takes to be at the forefront of new technology and be an expert.
Indeed, R is freely accessible as open-source software. It can be compiled and run on UNIX, Windows, and macOS. R allows programmers to extend the capabilities of the language by introducing user-specific functions.
What is Python?
Python is a programming language. It is an interpreted, object-oriented and high-level programming language. It is a common language used not just for coding. But also for websites and web application development, software development, and computer science education. Moreover, many people have also used it for scientific programming.
In other words, Python is one of the most popular dynamic programming languages. Python has been more widely used since Google created Python software called the Google App Engine.
However there are multiple versions of Python, but 2.7 is the most commonly used version. It’s an open-source language and is also popular with developers because it’s clear and straightforward.
Difference between R vs Python programming
Below are some differences between R vs Python programming languages.
R is a statistical language of programming and environment that combines statistics with visuals.
On the other hand, Python is a computer language that may use for data analysis and scientific computing.
The objective is the most crucial factor in the difference between R vs Python.
R programming includes several essential features for statistical analysis and representation.
Whereas, Python may use to create GUI programs, web applications, and embedded devices.
R programming offers several simple packages for doing out tasks.
On the other hand, Python is capable of doing matrix calculations as well as optimization.
Libraries and packages
The next factor is libraries and packages in the difference between R vs Python.
Several packages and libraries are available in the R programming, such as ggplot2, caret, and others.
Whereas, Pandas, Scipy, Numpy, and other vital libraries and packages include in Python programming.
The primary use of R is in data science for sophisticated data processing.
On the other hand, Data science initiatives require a more simplified methodology.
Integrated development environment
Rstudio, RKward, R commander, and other prominent R IDEs are listed here.
Whereas Spyder, Eclipse+Pydev, Atom, and other popular Python IDEs are listed here.
You need to know the suitable factor in the difference between R vs Python.
R is appropriate for statistical learning because it has robust data experimentation and exploration libraries.
On the other hand, Python excels in machine learning, large-scale web applications, and deep learning.
R has a somewhat sophisticated syntax, and the learning curve is not easy.
Whereas Python has a basic syntax that makes it simple to learn.
Similarities between R vs Python programming
R and Python are two of the most widely used languages for data analysis, machine learning, and scientific computing. These two can use for multiple programming-related tasks. Although these are not precisely similar, there are some common characteristics that both share. So, here is the list of five similarities between R and Python.
- Like R, Python is also interpreted and object-oriented programming language.
- Both R and Python are open-source and are freely available.
- They are open-source and very user-friendly, and have excellent community support.
- Both R and Python have a large and active global community.
- They have easy-to-use and install user interfaces.
We hope you enjoyed our article about Python vs R. Both Python and R are fantastic languages, and both have their own unique qualities. R and Python are two of the most popular programming languages data scientists use. Python is a dynamic programming language, while R is a functional programming language. They have several similarities but also several differences. Like Python, R is also an interpreted language. It is also a scripting language. R was designed to be used for statistical analysis, whereas Python was designed to be used for general programming.