This presentation tells about Python and R, their differences and their interconnection.

1. Python vs and R in
Data Science
Ravi Ranjan Prasad Karn
raviranjankarn@yahoo.com
Data Scientist

2. Python
 Python is a high-level general purpose language.
 It is developed by Computer programmers.
 One of the mottos of Python language is code readability.
 There is a way of writing Python program effectively. That is called Pythonic way of writing the
program.

3. R
 R is primarily a programming language for statistical computing and graphics.
 It is written by statisticians. The creators of R language are statistician who know
more about computers than their peers and they are computer programmers who
know more statistics than their peers.

4. Difference between Python and R
 Both Python and R have large software ecosystem and community for their use in Data Science. Both
are vastly used as Data Science tools. But there are few areas where one has advantages over other.

5. Area in which Python is better
 Deep Learning: Most of the Deep Learning researches such as Keras and Pytorch are implemented in
Python first.
 Model Integrating with other software: Models in Python can easily be integrated with other software and
can be deployed seamlessly because Python is general purpose language.
 Python has easy-to-read syntax. Code readability is one of the philosophies of Python language.
 Python emphasize on using idioms and write the code in a way called Pythonic way.

6. Areas in which R is better
 R is better in Statistical modeling research. This is because R is developed by Statisticians focusing
mainly on Statistics.
 Dashboarding is better in R. Shiny R has very nice visualization and dashboarding capabilities.

7. Ideas borrowed from each other
 plotline library for data visualization of Python is inspired by ggplot2 library of R.
 rvest library for web scarping in R is inspired by Beautifulsoup package of Python.