R Vs Python: Which is better and why?
R and Python are both open-source programming languages with a large community. New libraries or tools are added continuously to their respective catalog. R is mainly used for statistical analysis while Python provides a more general approach to data science.
R and Python are states of the art in terms of programming language oriented towards data science. Learning both of them is, of course, the ideal solution. R and Python requires a time-investment, and such luxury is not available for everyone. Python is a general-purpose language with a readable syntax. R, however, is built by statisticians and encompasses their specific language.
R vs Python: Comparing on 6 Parameters:

1.Usability:
R is generally suitable for any type of data analysis. The vast number of packages and readily usable tests make starting any analysis quite easy. R is the go-to language for data analysis tasks requiring standalone computing. It’s great for exploratory work, visualization, complex analysis, etc.
Python, on the other hand, is more suitable for implementing algorithms for production use. Being a full-fledged programming language, it provides greater flexibility while integrating data analysis tasks with web apps or if statistical code needs to be incorporated into a production database.
2. Flexibility:
Compared to Python it is easier to do complex analysis in R. In the case of R, a huge list of packages is available for implementing and statistical tests and models. While Python does come with libraries for statistical analysis, R is way ahead in the game. Python, on the other hand, comes with better integration options and a more streamlined approach to practicing novel tasks. Basically, Python is good if your data analysis project is part of a bigger project that involves many complexities while R is better for approaching data science in depth.
3. Popularity:

Python is a lot more popular than R. This is primarily due to the wide-scale usability of Python in comparison to R. Python can be used for many different purposes from web development to app development to data science. R, on the other hand, is made for core statistical analysis. Being a niche player it obviously less popular.
4. Ease of Learning:
R is the language for academicians and statisticians while Python is an all-purpose language usually preferred by programmers (people from the field of engineering and computer science). R has very steep learning, it is difficult to start with for non-programmers while Python has a more gradual learning curve. Both languages have good documentation, courses, and books available and their communities are well committed to driving growth to their respective languages.
If you want to know which is better to choose or you wish to know more about R and Python, you can have a look at the blog R vs Python: Which One Should You Use and Why?
