RStudio Blog

I absolutely LOVE Jupyter but I personally have found something better. I also love that Microsoft is behind making this happen with Jupyter.

RStudio's new feature to R is Notebooks and it is available in RStudio version 1.0+. It takes what is great about Jupyter Notebooks and adds easier version control and much easier to batch process your reports. Which are both huge wins for me.

http://rmarkdown.rstudio.com/r_notebooks.html

Blog Post: https://blog.rstudio.org/2016/10/05/r-notebooks/

"Interactive R Markdown

As an authoring format, R Markdown bears many similarities to traditional notebooks like Jupyter and Beaker. However, code in notebooks is typically executed interactively, one cell at a time, whereas code in R Markdown documents is typically executed in batch.

R Notebooks bring the interactive model of execution to your R Markdown documents, giving you the capability to work quickly and iteratively in a notebook interface without leaving behind the plain-text tools and production-quality output you’ve come to rely on from R Markdown."

How does RStudio have little interest in interoperability with other languages? They produce the reticulate package[1] to allow calling Python code for R, they have added support for Python to RMarkdown and RStudio[2], they let you host Python apps on their RStudio Connect product[3], they sponsor Ursa Labs to work on the Arrow project for easy data interchange[4].

1) https://rstudio.github.io/reticulate/
2) https://solutions.rstudio.com/python/
3) https://blog.rstudio.com/2020/12/16/rstudio-connect-1-8-6-python-update/
4) https://ursalabs.org/

NB: Here is a paper the derivation of the ggplot styles: http://vita.had.co.nz/papers/layered-grammar.pdf

I would recommend using theme_bw(), which helps solve some of the problem with the gray background.

EDIT: This is ggvis: http://blog.rstudio.org/2014/06/23/introducing-ggvis/

This is news to me, so I'll look into it to see how it differs from ggplot2.

EDIT 2: It seems more like that the difference is that ggvis is more for interactive charts, but then it requires a dependency on Shiny, which is not optimal for blog posts.

> The wave is subsiding and they now need to appear to have a viable business (so they can be sold to a bigger fish), which means there has to be a visible market they can sell into.

Might need a (2019) tag. As of 2020, RStudio is a Public Benefit Corporation and has a corporate structure that is designed for long-term investment in the scientific community, and isn't susceptible to buyout or IPO.

https://blog.rstudio.com/2020/01/29/rstudio-pbc/

(disclaimer: I work at RStudio)

> I haven't spent much time with dplyr, but I think it does a couple things

One of the cooler features in dplyr is the '%.%' operator which allows you to chain operations. So you can write something like this in dplyr:

Batting %.%
group_by(playerID) %.%
summarise(total = sum(G)) %.%
arrange(desc(total)) %.%
head(5)

which is very readable. That example stolen shamelessly from [1] ;)

[1] -- http://blog.rstudio.org/2014/01/17/introducing-dplyr/