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Wouldn't it be better to have a Python statistics library instead of creating a new language? When I looked at the documentation of R it looked very convoluted and it seems that my feeling is confirmed by other comments in this thread.

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Python is inherently not conducive to data analysis the same way R is. Python is not a lisp. R is more lispy, and its functional attributes make it incredibly useful for producing data analysis based code. For fully production ready systems R is not the ideal choice. For off the cuff analysis, python is a meager second.

Of course, these days Pandas is _the_ Python library for statistics. There is also scikit-learn.

http://pandas.pydata.org/

I haven't used R nor Pandas. How does the two compare? Why do people use R and not Python?

> Why do people use R and not Python?

R style DataFrames was raison d'etre of Pandas in the first place. (http://pandas.pydata.org/#why-not-r)

People started using R about the same time they started using Python (that is, the first half of the 1990s).

Since then, R has gained a huge number of statistics packages. Python has fewer of them.

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