The popularity of data science has often been credited to the increased data availability growing from static to live data, more powerful computing, and an emphasis on analytics-driven decisions made in businesses. The two most popular programming languages for data science are Python and R which are excellent tools in their own right but are very often conceived as rivals in the technological era. There have been many reasons that led to this outlook ranging from the diverse user base to the choice of the programming language used by them. What this leads to is an introduction and premises to the data science language camps the R-camp and the Python camp, each camp supported by a multitude of users who are in a constant duel trying to prove which language is the best. Both R and Python are supreme languages in their own regard, of late, Python has found greater applicability over the years and why is it so?