11–20 of 68 posts
we have recently started migrating to python from R because of notebooks and pyspark. I dont see us moving back anytime soon, because production code in python is orders of magnitude better than R. I just wish there was a decent dplyr for python though :(
I wish there was something like this for Python. Sure we have Jupyter/iPhyton and sure we have Spyder, but nothing even comes close to RStudio.
I wish there was something like this for Python. Sure we have Jupyter/iPhyton and sure we have Spyder, but nothing even comes close to RStudio.
Earlier quoted context omitted.
Funny, many people say this, but iPython notebooks have been around for a while (now called Jupyter Notebooks since they are not Python specific anymore) and it didn't spur a massive migration to Python...at least as far as I can tell. Not a bad thing, it's just R Notebooks kind of seem like old news to me. Addendum: I looked it up and it appears that Jupyter Notebooks actually have an R kernel ( https://irkernel.git…
Yeah but jupyter leaves bad taste in the mouth. Very frustrating to debug, binary file (no git/diff), much harder to layout than RMarkdown, no variable explorer. Additionally, the kernel idea is kind of lame/not implemented well. And you are getting nowhere in the data world without proper R support. There wasn't migration to python because there's a total lack of anything to migrate to in python. It has only textboo…
we have recently started migrating to python from R because of notebooks and pyspark. I dont see us moving back anytime soon, because production code in python is orders of magnitude better than R. I just wish there was a decent dplyr for python though :(
I haven't used dplyr much, is is not similar to pandas?
It explains it better than i can
Earlier quoted context omitted.
R Notebooks are such a killer feature!
Funny, many people say this, but iPython notebooks have been around for a while (now called Jupyter Notebooks since they are not Python specific anymore) and it didn't spur a massive migration to Python...at least as far as I can tell. Not a bad thing, it's just R Notebooks kind of seem like old news to me. Addendum: I looked it up and it appears that Jupyter Notebooks actually have an R kernel ( https://irkernel.git…
Most of our students use RStudio for their work. It's convenient and easy. For developing standalone scripts or functions, rather than notebooks or R Markdown files, the typical workflow is to write code in a file, then run it in the current R session by selecting pieces and hitting "Run".
But this encourages terrible practices. After a few iterations, the current environment does not reflect what's written in the file. If students write tests in a separate file, they neglect to source in their functions, because they're already in the workspace and so the tests run fine. Datasets that were loaded in the R console are used in code without being explicitly loaded there. Code gets changed without being run, or variable definitions are changed but old copies in the workspace accidentally used instead.
We end up getting many homework submissions that simply don't run if you start them in a new R session. Pieces are missing, code is out of order, tests only run if you manually select the test code and run it. It only worked in the R session of the original author.
R Markdown is a decent step, since rendering the HTML should start a session from scratch, but when we're asking them to write well-tested and modular algorithmic code, using R Markdown doesn't really fit.
I've begun to appreciate DrRacket's approach, where there is a "Definitions" pane and an "Interactions" window. When you Run the definitions, the current workspace is blown away and everything is defined from scratch from the Definitions, so there's no lingering state from REPL interactions. (Unfortunately your REPL history is lost, which can be annoying.) You can't run into the same inconsistent state as RStudio actively encourages.
I wish there was something like this for Python. Sure we have Jupyter/iPhyton and sure we have Spyder, but nothing even comes close to RStudio.
Check out Rodeo[0] from Yhat. Its not RStudio, but its an IDE with data science in mind. Been getting better and better each release. [0] http://rodeo.yhat.com/
Markdown is extremely limited (what we need is something more like knitr), there are quite a few bugs and it's difficult to access documentation of the packages.
I appreciate the work of the author, but all in all, it's nowhere near RStudio and - except for the fancy interface - actually behind Spyder.
I wish there was something like this for Python. Sure we have Jupyter/iPhyton and sure we have Spyder, but nothing even comes close to RStudio.
What are you missing in Spyder compared to RStudio?
A modern interface would also be nice.
And native support for Vim (I know there is a plugin but it's quite limited).
If you're looking into learning data science/visualization, RStudio is one of the best IDEs out there in that field. One of the reasons I switched to using Jupyter over R/RStudio directly was the native rendering of notebooks on GitHub, which made it pretty (example of mine: https://github.com/minimaxir/stack-overflow-survey/blob/mast... ) The addition of native R notebooks may make me switch back, although I'll have…