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It seems to depend on what you’re doing. Python definitely has more mindshare for machine learning, and particularly deep learning. However, that’s not all of
by mattkrause 8y ago
It seems to depend on what you’re doing.
Python definitely has more mindshare for machine learning, and particularly deep learning. However, that’s not all of statistics. For things like mixed-effects modeling, I think R still has a clear lead. There are some python packages (e.g., statsmodels) but R’s lme4 has more features, like custom covariance structures, and virtually every textbook and tutorial currently uses R. I’m actually not sure if I’ve ever actually encountered statsmodels in the wild. PyMCMC is relatively popular, but I think bugs/jags are also more common.
- peatmoss 8y agoAnd then there is the Zelig modeling framework for R that I can’t imagine not using after having used it. Don’t get me wrong, I like Python well enough, and knew it before I coded R. But Python is really behind R in stats support. I’d also add the tidyverse in there for general data munging. If I want libraries I’ll use R; if I want a programming language I love I'll use Racket or maybe Clojure; if I want some libraries and an okay programming language I’ll use Python, I guess.
- haskellandchill 8y agoWoa, thanks for pointing out Zelig, I needed that relogit and I didn't even know it :)
- peatmoss 8y agoThe counter factual simulation features are amazing and easy.
- haskellandchill 8y agoWondering why it hasn't got more publicity?