As I understand it, Matloff's point is "to each his own" and "understand relative strengths and weaknesses of open source projects, but be very careful about ma

As I understand it, Matloff's point is "to each his own" and "understand relative strengths and weaknesses of open source projects, but be very careful about making direct comparisons." Especially in the open source world, people like to compare competing solutions/software. While constructive comparisons help make software better, it is hardly ever productive to talk down on other open source projects. As far as "data science" environments go, I really think it comes down to your preference/needs, and a good understanding of the data/related concepts often outweighs the differences among various tools. Look no further than John Foreman's "Data Smart": he does a beautiful job dissecting and analyzing a wide range of datasets with...Excel.