4 R vs Python

4.1 Assignment operator: R

x <- 5;

7 -> y;

w <- x;

y -> z;

x = 5

y = 7

w = x

z = y

cat('x = ', x, '\n')

x = 5

cat('y = ', y, '\n')

y = 7

cat('w = ', w, '\n')

w = 5

cat('nz = ', z, '\n')

nz = 7


x = 'I am a string variable'

print('Title Case of the string x is: ', x.title())

Title Case of the string x is: I Am A String Variable

print('Number of occurrences of a in the string x is: ', x.count('a'))

Number of occurrences of a in the string x is: 4


x = 20

if x % 2 == 0:
  print('The number ', x, ' is EVEN')
else:
  print('The number ', x, ' is ODD')

The number 20 is EVEN

R base includes many functions available to use instantly without installing any libraries

install.packages('ggplot2)

library(ggplot2)

Python needs installation of libraries for efficient usage

pip install matplotlib

import matplotlib.pyplot as plt

R has in-built object orientation framework, but one can do most of the standard jobs by using R as a procedural language.
Python object orientation framework is similar to other programs like C, C++, and hence easy to implement. Many standard pipeline can be developed seamlessly using classes in Python.