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That seems like you could simply use http://jupyter.org/ http://jupyter.org/ and just run the script with R code inline. http://blog.revolutionanalytics.com/20

by baldfat 10y ago

That seems like you could simply use http://jupyter.org/ http://jupyter.org/ and just run the script with R code inline. http://blog.revolutionanalytics.com/2016/01/pipelining-r-python.html http://blog.revolutionanalytics.com/2016/01/pipelining-r-pyt... Also why not just switch to Pandas it really is a pretty close R clone.

blahi 10y ago
How much experience do you have in statistical computing, out of curiosity?
nerdponx 10y ago
It has nothing to do with interoperability on my machine. I use notebooks (and Pandas) all the time, and I consider myself fluent in bith R and Python. It's because R is a substantial engineering dependency. As I said, our entire stack is Python and Node. Yes, you can call R from Python using Rpy2, but that's a pro-bono project maintained largely by one person. It's great for casual use, but there is far too much risk to start talking about building critical business code around it.
- baldfat 10y ago
  So why not Pandas?
  - nerdponx 10y ago
    Personal preference. I switch back-and-forth based on the project. R data frames are native and feel native. Pandas data frames are non-native and can be a pain in the ass to work with. That, and there is a lot mpre to the decision than just which data frame implementation I like better.
kgwgk 10y ago
"Pretty close" as long as you stay within the region of common functionality. I wouldn't say it's a clone.
- baldfat 10y ago
  That is true. I actually started my journey with Pandas and then switched to R for the ecco-system and zero based for data science drove me nuts. But I do feel that the goal is a clone. "Python has long been great for data munging and preparation, but less so for data analysis and modeling. pandas helps fill this gap, enabling you to carry out your entire data analysis workflow in Python without having to switch to a more domain specific language like R." http://pandas.pydata.org/ http://pandas.pydata.org/

by baldfat 10y ago

blahi 10y ago

How much experience do you have in statistical computing, out of curiosity?

nerdponx 10y ago

It has nothing to do with interoperability on my machine. I use notebooks (and Pandas) all the time, and I consider myself fluent in bith R and Python. It's because R is a substantial engineering dependency. As I said, our entire stack is Python and Node. Yes, you can call R from Python using Rpy2, but that's a pro-bono project maintained largely by one person. It's great for casual use, but there is far too much risk to start talking about building critical business code around it.

baldfat 10y ago
So why not Pandas?
- nerdponx 10y ago
  Personal preference. I switch back-and-forth based on the project. R data frames are native and feel native. Pandas data frames are non-native and can be a pain in the ass to work with. That, and there is a lot mpre to the decision than just which data frame implementation I like better.

kgwgk 10y ago

"Pretty close" as long as you stay within the region of common functionality. I wouldn't say it's a clone.

baldfat 10y ago
That is true. I actually started my journey with Pandas and then switched to R for the ecco-system and zero based for data science drove me nuts. But I do feel that the goal is a clone. "Python has long been great for data munging and preparation, but less so for data analysis and modeling. pandas helps fill this gap, enabling you to carry out your entire data analysis workflow in Python without having to switch to a more domain specific language like R." http://pandas.pydata.org/ http://pandas.pydata.org/