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
Thanks to Google's Season of Docs program for supporting @rOpenSci's R-Universe!
R-Universe is our platform for testing, building, distributing, and discovering R packages and documentation, led by the incomparable @jeroenooms. With this support, @maelle will be leading a a comprehensive overhaul of our docs to make R-Universe easier and more accessible for both users and developers.
@jpeelle @rstats
Like "heatmap" is correct for "value Z As color against params x and y", but depending on what it is it there are more specific names - it doesnt look like a correlation matrix, but it does look like a 2D probability density. If youre not already using it, the answer is https://ggplot2.tidyverse.org/reference/geom_density_2d.html
#posit I’m still considering whether to attend posit conference 2024. I’d like to attend the career fair to look for data science related jobs, meanwhile listening some talks. But the ticket is still expensive even for the students, I applied for Opportunity Scholarships but haven’t got any replies from @Posit till now. I doubt is it worthwhile to spend $1198 on a 3-day conference mainly for the career fair? Can anyone have some experiences of posit give some advice? Really appreciate it @rstats
@ai4blobcat oh yeah, I see. Sorry I saw your (@Lluis_Revilla) post first and missed the job-seeking angle. We do have lots of activities that encourage networking, but I don’t think we’ve done anything specifically for people looking for a job. It’s worth considering! I’ll pass this along to the planning committee.
In the replies, they also mentioned @yihui , a very famous software engineer worked for RStudio but got laid off recently, he is also on mastodon. I was also very shocked when I first heard this news.
Anyway, sum them up, it seems a great opportunity for networking, but not for job-seeking only
We dive deep into simplifying outlier detection in R using #easystats to follow good practices and make your data analysis more robust and replicable. Check it out! #Rstats#DataAnalysis@rstats
The {tidyHeatmap} #rstats 📦 “introduces tidy principles to the creation of information-rich heatmaps.”
“For plotting, you simply pipe the input data frame into heatmap, specifying:
The rows, cols relative column names (mandatory)
The value column name (mandatory)
The annotations column name(s)”
By Stefano Mangiola https://github.com/stemangiola/tidyHeatmap @rstats
I probably don’t say it enough, but I’m really thankful for @R4DSCommunity and @jonthegeek. For the past 2+ years, this community has really been a godsend to me not only for the knowledge I’ve gained but the friends I made along the way as well. Thank you, Jon, for all you do to keep us all learning and growing together!
@lydz_gibby@R4DSCommunity@jonthegeek@rstats This community is great. I have learned a lot from the community and really thankful to everyone's compassion in helping me and others.
I'm setting up a new more powerful Mac work system today, and it's very odd that my R sessions keep crashing when working with large data sets in RStudio. This didn't happen on the older, less capable Mac and it's not happening when I run the same scripts in VS Code.
I don't have time to trouble-shoot this, I'm just going to run those scripts in VS Code. But it's odd. Wonder if anyone else has experienced this and if there's a way to allocate more memory to #RStudio @Posit@rstats#rstats
A bit late, but {rempsyc} @rstats package v0.1.7 has been on CRAN for a while now! Since the last version, this contains bug fixes, adjustments to APA reporting, and many other minor #rstats improvements. 🧵
@rstats Still for nice_table, (4) z” and “Z” are now formatted to two digits instead of zero digits to comply with the Wald Z statistics in SEM (with lavaan and lavaanExtra); (5) now supports conversion of “CI_lower_B” and “CI_upper_B” columns to “95% CI (b*)”.
@rstats APA 7th edition actually advises against using beta to represent standardized coefficients, but suggests instead to use a lowercase italic b followed by an asterisk: b*. rempsyc now follows this APA recommendation.
