Here in this article, we will discuss the comparison between Python and R language, and pros and cons between R and Python Programming Language.
Let us compare Python and R languages on different criteria, one by one:
Availability and cost
R and Python are completely free.
R has the steepest learning curve, so it becomes necessary to learn to code. It is a low - level language, so simple procedures can take longer codes. On the other hand, Python is known for its simplicity.
R computations are limited to the amount of RAM on 32 - bit PC
Graphical Capabilities of R is advanced
Advancement in tools
Both the languages are open in nature and contributions. So in the latest developments, there are more chances of error.
R slow and it is designed to so to make data analysis and statistics easier. But this makes life on a computer more difficult. We need to define how implementations work. Also, R is poorly written.
Python and R are good for start-ups and companies looking for cost efficiencies.
Customer Service support
None of these have this facility. In the time of any trouble, you are on your own.
Let us Discuss some pros and cons of both Python and R separately
Free availability and stability
Easy integration with extensible using C and Java
Supports multiple Systems and Platforms
Easy to learn even for a novice developer
Ample of resourced available
A comparatively smaller pool of Python Developers
Not Good for Mobile Development
Database access Limitations
Slower speed than C or C++
Comprehensive Statistical Analysis Package. New ideas mostly appear in R
Open Source. Anyone can use it
Suitable for GNU/Linux and Microsoft Windows. It also has cross platforms which can run on many operating systems.
Anyone can do bug fixing and code enhancements
Quality of some Packages is not Good
If something doesnâ??t work, there is no one to whom we can complain
People devote their own time developing it
R can consume all the memory because of its memory management