From both Programming Languages R and Python: Which is best for Machine Learning?

By ridhigrg |Email | Jun 7, 2019 | 2904 Views

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.

Learning Ease
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.

Data Handling
R computations are limited to the amount of RAM on 32 - bit PC

Graphical Capabilities
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.

Speed
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.

Job scope
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
Python Pros
  • 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

Python Cons

  • A comparatively smaller pool of Python Developers
  • Software performance
  • Not Good for Mobile Development
  • Database access Limitations
  • Slower speed than C or C++

R Pros
  • 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

R cons
  • Quality of some Packages is not Good
  • If something doesn??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

Source: HOB