'There is a healthy debate raging over the best language for learning data science. Many people believe it's the statistical language R. (We call those people wrong).' (Data Science from Scratch, Joel Grus, O'Rielly Press).
People have strong opinions but what does the data say? It is difficult to make a direct comparison because while R is a statistical scripting language with narrow usage, Python is a general purpose language and is used in areas that have nothing to do with data science for example Python is beginning to replace PHP in some back end web development. But we can look at some different web resources to see how popular the two languages are.
Google trends: both languages show an increase in interest since 2011 but the increase for Python is stronger than for R.
TIOBE: R is ranked 18, up 1 from last year while Python is ranked 5 up 3 since last year. Python won best rise in ratings in 2007 and 2010.
PYPL: Python is ranked 2 and going up. R is ranked 9 and going up.
The above suggests that both languages continue to grow in popularity. Python is more popular (but then it has other uses outside of data analysis). Perhaps the best strategy is choose whichever language you feel most comfortable with and learn it to the best of your ability but don't ignore the other language because both are used extensively in data science.
This blog includes:
Scripts mainly in Python with a few in R covering NLP, Pandas, Matplotlib and others. See the home page for links to some of the scripts. Also includes some explanations of basic data science terminology.