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I agree, 120%.

I like the r approach so much more.

I mean, as a medium for interactive exploration where you might want graphs and widgets or other rich/dynamic output, I still think the notebook is superior. But as a medium for developing complete, share-able, reproducible data analyses, I do think R has the upper hand.

Graphs, widgets and other rich/dynamic output is also possible with the R approach.

https://rmarkdown.rstudio.com/

Additionally, Rstudio is an incredibly powerful IDE for data analysis.

EDIT: Interestingly, however, I still use ESS https://ess.r-project.org/ but that's because I love Emacs too much :D

I understand. I believe I pointed that all out my comment above. I wasn't saying that I find the notebooks superior because they allow for rich & dynamic output, but that I find it superior to RStudio when all you want is a quick exploratory REPL capable of rich/dynamic output. I simply find it easier to fire up a notebook and start noodling around than writing an RMarkdown notebook. That really only holds if I'm not overly concerned with keeping or sharing the notebook. Otherwise, I believe RMarkdown is the better option.

I also tend gravitate towards ESS, and probably split my R development time between emacs and RStudio. I've even written a very kludgy Rmd notebook mode that uses overlays to show evaluation results from code chunks. But RStudio is very well-designed and ESS just doesn't compare feature-wise, sadly.

I just like python pandas better than R.

Not me. I'd take dplyr and related libraries over pandas any day. I've been using pandas for 6 years and I'm still regularly tripped up by parts of its API.

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