R programming and Python are both used extensively for Data Sciences. Both are very useful and open source languages as well.
R Language is used for machine learning algorithms, linear regression, time series, statistical inference, etc. It was designed by Ross Ihaka and Robert Gentleman in 1993.
R is an open-source programming language that is widely used as a statistical software and data analysis tool. R generally comes with the Command-line interface. R is available across widely used platforms like Windows, Linux, and macOS. Also, the R programming language is the latest cutting-edge tool.
Python is a widely-used general-purpose, high level programming language. It was created by Guido van Rossum in 1991 and further developed by the Python Software Foundation. It was designed with an emphasis on code readability, and its syntax allows programmers to express their concepts in fewer lines of code.
Below are some major differences between R and 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 application and web application as well as with embedded systems|
|Work ability||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 more streamline approach for data science projects.|
Program for addition of two numbers:
The sum is 12
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