Should you learn Phyton or R ? - For Aspiring Data Science Students

Why Python is preferred for data science

• Guido van Rossum created Python
• Python was released in 1989. It has been around for a long time, and it is object-oriented
• IPython / Jupyter’s notebook IDE is excellent.
• There’s a large ecosystem. For example, Scikit-Learn’s page receives 150,000 – 160,000 unique visitors per month.
• There’s Anaconda from Continuum Analytics, making package management very easy.
• The Pandas library makes it simple to work with data frames and time series data.

Why R is preferred for data science

• John Chambers created R and prior to that he created S
• R was created in 1992, after Python, and was therefore able to learn from Python’s lessons.
• Rcpp makes it very easy to extend R with C++.
• RStudio is a mature and excellent IDE.
• CRAN has many machine learning algorithms and statistical tools.
• The Caret package makes it easy to use different algorithms from 1 single interface, much like what Scikit-Learn in Python

I started by learning R and then picked up Phyton. I personally think Phyton is much more versatile than R but it is good to learn both the languages.