It would enable the relatively easy creation of serious games and interactive exercises to learn R or statistics (or with the {rock} package, qualitative research); combining R with a simple game/adventure engine.
Check out the issue by Samuel Joseph Haynes labelled 'help wanted':
"Check the suitability of the vignette colour scheme for accessibility" at https://github.com/ropensci/tidyqpcr/issues/94
{tidycensus} #rstats 📦 creator Kyle Walker: "Want all 8.13 million US Census blocks available for your #GIS project? It's a one-liner in #rstats thanks to the tigris and purrr packages:
us_blocks <- purrr::map_dfr(c(https://t.co/RfFgUSx1a6, "DC"), ~tigris::blocks(state = .x, year = 2023))
Downloading will take time; set options(tigris_use_cache = TRUE) beforehand to build a local cache of block shapefiles that you can access without having to download."
Hmm, I'm having trouble connecting to the @Posit package manager at the moment. I get: Warning: unable to access index for repository <https://packagemanager.posit.co/cran/latest/src/contrib>: cannot open URL '<https://packagemanager.posit.co/cran/latest/src/contrib/PACKAGES'> Is anyone else in the #RStats community seeing this? @rstats
The {summarytools} #rstats 📦 aims to:
“Provide a coherent set of easy-to-use descriptive functions [like] those in commercial statistical software suites such as SAS, SPSS, and Stata
“Offer flexibility in terms of output format & content
“Integrate well with commonly used software & tools for reporting”
Results can be displayed in console or rendered/saved as HTML, plain text, or R Markdown. By Dominic Comtois https://htmlpreview.github.io/?https://github.com/dcomtois/summarytools/blob/master/doc/introduction.html #EDA@rstats
File import/export in R is simple and elegant with the {rio} #rstats 📦. It uses just 2 main functions for dozens of file types: import() and export(). Whether .zip, .xlsx, Google sheets, json, .rds, .csv or more, rio handles file-extension checks and selecting the right functions. http://gesistsa.github.io/rio/
There's also a convert() function.
One of my favorite R packages!
By Thomas J. Leeper, Chung-hong Chan, David Schoch & Jason Becker @rstats
@schochastics@jmcastagnetto@rstats@chainsawriot In my R book for journalists (Practical R for Mass Communication and Journalism), I decided to start off with "here are some super cool things you can do with very little code!" to get people enthusiastic and engaged. In general, I like to start with well formatted data, making very clear to people that this is unlikely to be what they encounter in the real world. I like to ease into it, but I 💯 admit that other approaches are valid 2/2
Yes, I agree with that approach, giving them a taste of what can be done, then working with them to get there.
In our case, we show reports, tables, graphs that are of use for health surveillance, then we go step by step in each session on each aspect: reading data, exploring it, cleaning it, making tables, calculating statistics, making charts, etc., and we try to show some of "warts" in the data along the way, so it is more tangible to them.
The {styler} #rstats 📦 “formats your code according to the tidyverse style guide (or your custom style guide) so you can direct your attention to the content of your code. It helps to keep the coding style consistent across projects and facilitate collaboration.” By Lorenz Walther & Kirill Müller