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Hi, very nice guide. I work full time as a data person with Python3 + data stack (pandas, etc.) on Mac OSX and it's pretty stable, also it's probably recommended to default to Py3k and mention Python 2.7 as an "if all else fails" alternative.
Also, it's probably a better idea to install things via pip rather than brew since that way you skip the extra layer – plus there might be useful libraries that aren't available via Homebrew so you're stuck with pip anyway.
What do you think?
The text was updated successfully, but these errors were encountered:
@sb2nov@myyc This could solved using pyenv (similar to rbenv) https://github.com/yyuu/pyenv
You could install anaconda3 and anaconda2 in the same directory. Use anaconda3 as your primary python version and anaconda2 as a fail-safe. This way you don't need to install so many packages with brew or pip. I mention anaconda since you're doing data analysis, but you could also do python3 and python2 instead.
I can submit a PR that mentions pyenv as an alternative way to install Python. Personally, it's been a lifesaver for me!
Hi, very nice guide. I work full time as a data person with Python3 + data stack (pandas, etc.) on Mac OSX and it's pretty stable, also it's probably recommended to default to Py3k and mention Python 2.7 as an "if all else fails" alternative.
Also, it's probably a better idea to install things via
pip
rather thanbrew
since that way you skip the extra layer – plus there might be useful libraries that aren't available via Homebrew so you're stuck withpip
anyway.What do you think?
The text was updated successfully, but these errors were encountered: