>Hadoop is definitely happening but it’s Google’s problem because now after building our own Hadoop on iron solution, after dealing with Redshift for a while, we now just gave it all to BigQuery.
A tidy simplification of the technology stack.
I've experienced this in my own work as well. The extra verbosity of Pandas data frames compared to R data frames doesn't bother me anymore. Sometimes I miss the Lispy homoiconic magic, but not enough to make me want to use R at work.
I still use it once in a while for heavily "statistical" stuff that doesn't ever need to be "productionized", but for run-of-the-mill machine learning I see no reason to use it over Pandas.
I'd like to have my cake and eat it too, but I'm worried that's too good to be true.
Not to mention writing R-like code in Python will prevent you from being immediately understood by both R and Python developers. It's just not worth it.
I just want to acknowledge this fabulous phrase.