.

Also know, how useful is R language?

R is essential in data science because of its flexibility in the field of statistics. It is usually used in biology, genetics as well as in statistics. R is also a vector programming language. R is good for business because it is open-source and great for visualization.

Also, should I learn R or Python? In a nutshell, he says, Python is better for for data manipulation and repeated tasks, while R is good for ad hoc analysis and exploring datasets. R has a steep learning curve, and people without programming experience may find it overwhelming. Python is generally considered easier to pick up.

Also asked, is R programming easy to learn?

As many have said, R makes easy things hard, and hard things easy. However, add-on packages help make the easy things easy as well. Like most other packages, R's full power is only accessible through programming. The two which are most like SAS Studio, SPSS or Stata are R Commander and Deducer.

What are the limitations of R?

Disadvantages of R Programming

• Weak Origin. R shares its origin with a much older programming language “S”.
• Data Handling. In R, the physical memory stores the objects.
• Basic Security. R lacks basic security.
• Complicated Language. R is not an easy language to learn.
• Lesser Speed.
• Spread Across various Packages.