RStudio Blog

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.

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."

> 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 think this is one area where rstudio has the lead. https://blog.rstudio.com/2020/09/30/rstudio-v1-4-preview-visual-markdo…

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-updat… 4) https://ursalabs.org/

His example is poor. dplyr wasn’t even at 1.0 in 2016. It was only 0.50: https://blog.rstudio.com/2016/06/27/dplyr-0-5-0/. Of course one might expect breaking changes in a maturing package.

Hi Andrew! Looking into similar requirements I came across Feather and fst. They both basically let you efficiently slice into compressed on-disk DataFrames. Feather already supports Python, but fst is just for C++ and R at the moment. https://blog.rstudio.com/2016/03/29/feather/ http://www.fstpackage.org/ https://github.com/fstpackage/fstlib

Background jobs in Rstudio are coming: https://blog.rstudio.com/2019/03/14/rstudio-1-2-jobs/ Also not sure you can criticize a whole language because some random code you read doesn’t have comments.

You can use RStudio Connect to publish Jupyter notebooks, see https://blog.rstudio.com/2019/01/17/announcing-rstudio-connect-1-7-0/

RE python in Rmarkdown being limited... > The Python session ends after the cell executes, making it unhelpful for tasks other than ad hoc scripts. This isn't the case anymore thanks to the reticulate library. https://blog.rstudio.com/2018/03/26/reticulate-r-interface-to-python/

> No inline rendering of markdown. That's incorrect, take a look here -> https://blog.rstudio.com/2016/10/05/r-notebooks

I will check it out. You can also use R notebooks to embed SQL code in notebook format. https://blog.rstudio.org/2016/10/05/r-notebooks/ (scroll down to "Batteries included") I was playing around a bit with it: https://carlosror.github.io/baseball_mysql/

The "Hadley Wickham Universe", yeah, his stuff is awesome. magrittr and rvest are more awesomeness from Hadley that make web scraping a pleasure. [1] [1] http://blog.rstudio.org/2014/11/24/rvest-easy-web-scraping-with-r/

> 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/