R programming and python has become popular in the field of analytics whether you are data analyst data scientist or machine learning engineer you use this language in this article I am going to tell you about what are the differences between r and Python and which language is the best programming language for data science and doing analysis:
Here are some Key Differences between R Programming and Python:
1. R programming is a free software environment for statistical computing while Python is an open source scripting language with built-in object-oriented programming.
2. R programming was created by Ross lega and Robert gentleman in 1995 as an implementation of a programming language the purpose of developing this language is to deliver a better and more user friendly way to do analysis while Python was created by Edwin Rossum in 1991 the purpose of developing python language is to emphasize more on code readability.
3. If you want to do analysis and if you are a beginner then it seems to be difficult but if you have a statistical background then you can prefer R programming else if you are a beginner in the field of analytics and want to do analysis than python as a good programming language to start with.
4. R programming has a rich community of over more than 2 million users across the world the mean is a strength is that community members help you to optimize your code while Python community slightly less powerful and is gaining acceptance of a good number of StackOverflow members.
5. If you want to work in development R studio is preferred it has package like plyr,dplyr are the packages for manipulating of data while in Python there are number of development environment like a spider, ipython notebook and if you are willing to start your analysis journey then there are many libraries like numpy, Scipy, matplotlib and sklearn are the essential libraries to do analysis in Python.