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If you use data science libraries like numpy, pandas etc then these rely on OS level packages like libgfortran and liblapack. Anaconda is a way to guarantee you are running a known stack from dev machine through to production. This is the key benefit IMO (as well as getting improving deploy times)

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All these packages provide wheels on OS X, there is no need to install gfortran these days.

A good point about a known stack.

Many people who do data science on OS X have to deploy or scale their things on Linux servers. Or serve Python scripts to collaborators on Windows.

Even if you are a working on an island and you fully control your own dev and production environments, there are myriad subtle divergences between the build toolchain on Linux and BSD/Darwin that can trip you up.

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