#rstats #python #gis folks I could do with some advice. I'm working with the fast {cppRouting} library on generating millions of leastcost paths from graph objects. The paths are output as data frames in the form of `data.frame(from = ..., to = ...)`. With large graphs the resulting data.frames can be many millions of rows long. The next stage is to convert to line geometries and then 'burn' to raster showing number of times each cell is traversed. 1/2
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Looks like better observability for #rstats is coming! @gaborcsardi is developing an opentelemetry R package that provides an interface to #OpenTelemetry - enabling R users to instrument their code with traces, metrics & logs in a vendor-agnostic way.
GitHubGitHub - r-lib/opentelemetry: R API for OpenTelemetryR API for OpenTelemetry. Contribute to r-lib/opentelemetry development by creating an account on GitHub.
Explore the blog series on comparing spatial patterns in raster data using R. 
- Techniques for analyzing continuous and categorical data
- Handling overlapping and arbitrary regions
- Advanced methods for comparing spatial patterns
Find the full series at https://buff.ly/s35030O
#RStats poem
It’s so nice
to wake up in the morning
all alone
and see email from CRAN–
R-CMD-check
is not passing
any more.
Dynamically Load Assembler Code in R : https://yumechi.jp/en/blog/2024/dynamically-load-assembler-code-in-r/
simple R SEXP in rust : https://github.com/eternal-flame-AD/typed-sexp
#Rstats #assembly #rust #coolandcrazy
Yumechi · Dynamically Load Assembler Code in RAn attempt at making R load and execute assembler code on the fly.
I created an R package that makes it easy to create Tabsets in Quarto. #RStats #quarto
https://sayuks.github.io/quartabs/
sayuks.github.ioquartabs
@rOpenSci and @openscapes plan to host a networking event for US scientists and others affected by recent layoffs.
We are looking for co-hosts who
- transitioned from government to other sectors
- are in fields adjacent to statistics/data science/research software engineering
- are willing to participate in a 1-1.5 hour virtual event (date TBD)
- are able to answer follow-up questions and/or do resume reviews
If this is you or close to it, please get in touch!
Me and sf really don't get along. #RStats
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Others looking at future directions in teaching research software may be interested in this blog post that covers both the decisions and the process of updating lesson software recommendations with @thecarpentries #rstats #python #bash #git
The {grafify} #RStats 
aims to make it easier for new or experienced R users to:
* "plot great-looking graphs with few lines of code while exploring data"
* "apply colour blind-friendly palettes to graphs plotted with grafify or ggplot2"
& more. By Avinash Shenoy
https://grafify.shenoylab.com/
We (NHS-R Community Team) are seeking volunteers to host/co-host webinars and/or workshops throughout the year. This is a fantastic opportunity to share your knowledge and skills whilst building a community of practice for data analysis and data science using open source software.
If you would like to volunteer or recommend someone within your network to contact, please email the NHS-R Community inbox (nhs.rcommunity@nhs.net).
{ggblanket}, a wrapper around #ggplot for quick, explorative plots with sensible defaults and less code. https://davidhodge931.github.io/ggblanket/ #rstats
davidhodge931.github.ioSimplify ggplot2 VisualisationSimplify ggplot2 visualisation with ggblanket wrapper functions.
TFW when a GitHub issue you submitted in 2017 (and have absolutely no recollection of making) suddenly results in a flurry of emails and an implemented fix within 24 hours, in March 2025. I need to get back and look at this. #rstats
https://github.com/r-tmap/tmap/issues/154#issuecomment-2711051886
GitHubDealing with date/time stamps as a continuous variable · Issue #154 · r-tmap/tmap
I've found the perfect way to make #rstats programmers scream in existential terror. Behold zero-indexed R!
Redefining reality with <15 lines of code is so hot right now.
Now watch as I calmly refer to v[0] while maintaining direct eye contact.
![A screenshot showing the redefinition of subset operators in R to allow for 0-based indexing by globally shifting index starting locations by +1.
Source code follows:
----
# Subset ----
# Save original subset operators
original_bracket <- `[`
original_double_bracket <- `[[`
# Create zero-based versions of subset operators
`[` <- function(x, i, ...) {
if (is.numeric(i) && length(i) > 0 && !all(is.na(i))) {
i <- i + 1
}
original_bracket(x, i, ...)
}
`[[` <- function(x, i, ...) {
if (is.numeric(i) && !all(is.na(i))) {
i <- i + 1
}
original_double_bracket(x, i, ...)
}
# Demo ----
v <- c("a", "b", "c")
v[0]
#> [1] "a"
my_name_is <- function(name) {
paste("My name is", name[0])
}
my_name_is(c("coatless", "r", "james"))
#> [1] "coatless"](https://files.mastodon.social/media_attachments/files/114/146/451/315/288/563/original/55ad575f6c147ba0.png "A screenshot showing the redefinition of subset operators in R to allow for 0-based indexing by globally shifting index starting locations by +1.
Source code follows:
----
# Subset ----
# Save original subset operators
original_bracket <- `[`
original_double_bracket <- `[[`
# Create zero-based versions of subset operators
`[` <- function(x, i, ...) {
if (is.numeric(i) && length(i) > 0 && !all(is.na(i))) {
i <- i + 1
}
original_bracket(x, i, ...)
}
`[[` <- function(x, i, ...) {
if (is.numeric(i) && !all(is.na(i))) {
i <- i + 1
}
original_double_bracket(x, i, ...)
}
# Demo ----
v <- c(\"a\", \"b\", \"c\")
v[0]
#> [1] \"a\"
my_name_is <- function(name) {
paste(\"My name is\", name[0])
}
my_name_is(c(\"coatless\", \"r\", \"james\"))
#> [1] \"coatless\"")
New blog post about data art!
Have you ever wondered:
What is data-driven art?
Why do people make data art? How do I get started making my own?
Then this blog post is for you! 
It includes an example using #TidyTuesday data - with code in both #Python and #RStats!
Nicola RennieCreating data-driven art | Nicola RennieIf you've ever wondered what data-driven art is, or why people make it, then reading this blog post should help to answer those questions. It also includes an example of data-driven art, which can be created in Python or R, and talks through the process of getting started with your own art.
I'm super happy to see that several of my data visualisation projects were long-listed at the 2024 Information is Beautiful Awards!
Check out the full longlist here: https://www.informationisbeautifulawards.com/showcase?action=index&award=2024&controller=showcase&page=1&pcategory=long-list&type=awards
GIF
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The course is open source:
https://github.com/a-nap/Digital-Research-Toolkit
I will be updating it every week with slides, code, and homework assignments.
#AcademicResearch #DigitalHumanities #Linguistics hashtag #DataScience #Rstats #AcademicChatter #Academic
Process spatial data and create reproducible maps with R using "Cartography with R" by Timothée Giraud. Covers R Spatial, data manipulation, thematic maps, and more.
Read it at: https://buff.ly/sIqGXss
