Earlier quoted context omitted.
Python has gotten sufficiently weapons grade that we don’t descend into R anymore. 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 "productio…
Would anyone recommend / warn against any of python tidyverse ports, like dplython (dplyr) or plotnine (ggplot2)? I'd like to have my cake and eat it too, but I'm worried that's too good to be true.
Data Science at The New York Times
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Re: Data Science at The New York Times
#12Re: Data Science at The New York Times
#13>Python has gotten sufficiently weapons grade that we don’t descend into R anymore. >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.
Python has gotten sufficiently weapons grade that we don’t descend into R anymore. 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 "productio…
I just want to acknowledge this fabulous phrase.