sayuks
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sayuks.bsky.social
sayuks
@sayuks.bsky.social
12 followers 190 following 2 posts
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Reposted by sayuks
eddelbuettel.com
duckdb-mlpack 0.0.2: mlpack is now a duckdb community extension
Bringing mlpack machine learning to duckdb SQL
dirk.eddelbuettel.com/blog/2025/10...
Screenshot of blog post at https://dirk.eddelbuettel.com/blog/2025/10/26#duckdb-mlpack_0.0.2 announcing that mlpack is now a duckdb community extension
October 26, 2025 at 1:58 PM
Reposted by sayuks
coreysparks1.bsky.social
ok, dumb #rstats question. I'm using #quarto and i want to print some inline R code in my HTML report, but I DON'T want it to actually run the code

I want it to be like this in the report:
`r mean(1:10)`
September 5, 2025 at 4:26 PM
Reposted by sayuks
ellakaye.co.uk
Once again, @davisvaughan.bsky.social's extrachecks have saved me from a likely CRAN rejection for an upcoming #RStats package submission. Thanks Davis! github.com/DavisVaughan...
GitHub - DavisVaughan/extrachecks
Contribute to DavisVaughan/extrachecks development by creating an account on GitHub.
github.com
September 3, 2025 at 7:57 PM
Reposted by sayuks
coatless.bsky.social
Prototyping #rshiny apps to native #electron desktop apps:

shinyelectron::export() → #rshinylive conversion → .dmg → Native Mac app

Zero #rstats dependencies for end users! Early days but promising 👀
September 4, 2025 at 7:35 AM
Reposted by sayuks
yutakanzawa.bsky.social
先程の #TokyoR の初心者セッションのスライドです。ご査収下さい。

R & RStudio入門
ytknzw.github.io/TokyoR/%E5%8...

データハンドリング
ytknzw.github.io/TokyoR/%E5%8...

データ可視化
ytknzw.github.io/TokyoR/%E5%8...
ytknzw.github.io
June 21, 2025 at 8:02 AM
Reposted by sayuks
marcdotson.com
There are a lot of introductions to Python, but this one is mine. It includes a walkthrough of using uv for environment management, Polars for data wrangling, seaborn.objects for visualization, and scikit-learn for modeling. #rstats #python #pydata
An introduction to Python for R users – Occasional Divergences
This introduction to Python assumes you know R, which is used as an analogy to explain Python for data analysis.
occasionaldivergences.com
June 14, 2025 at 12:43 AM
Reposted by sayuks
smachlis.bsky.social
The {listviewerlite} #RStats 📦 "provides a single function listview(), which creates a collapsible tree view of R lists using only HTML and CSS, without the need for JavaScript." On GitHub. By Long Nguyen
long39ng.github.io/l...
gif shows clicks to open a 'tree' view of a list with child branches
June 7, 2025 at 12:28 PM
Reposted by sayuks
smachlis.bsky.social
Rainy day here, so I'm using #GenerativeAI to help teach me more about @kylewalker.bsky.social 's cool {mapgl} #RStats 📦 . And it's been pretty fun so far 😀 1/3
Instead of starting with data and aesthetics, mapgl thinks like this: Map canvas first - you create a base map (like a Google Maps background) Add data as "sources" - your sf objects become data sources Add "layers" that reference those sources - these are like geoms but work differently Style with expressions - not aesthetics, but JavaScript-style expressions This is more like how a web developer builds an interactive map, which is why it's so powerful for complex visualizations. Before I show you the syntax, let me test your intuition: If you had to guess, how do you think you'd start building a mapgl map differently than a ggplot? What do you think comes first - the data or something else? And here's a follow-up: Given that mapgl creates interactive web maps, what do you think might be the equivalent of choosing your x and y variables in ggplot2?
June 7, 2025 at 6:18 PM
Reposted by sayuks
mattansb.msbstats.info
When awesome packages come together 💥

#rstats
January 3, 2025 at 6:23 AM
Reposted by sayuks
pdalgd.bsky.social
A fairly clean way is to make a pkglist of the installed.packages() that are not Priority "base" or "recommended", store it somewhere, then install.packages(pkglist) after upgrading.
April 24, 2025 at 8:26 PM
Reposted by sayuks
andrew.heiss.phd
Here it is with real data! A map of 550,000 foreign aid projects in just a few lines of #rstats code
library(tidyverse) library(sf) library(rnaturalearth) library(here) # GODAD data from https://godad.uni-goettingen.de/data/ project_level <- read_csv( unz( here("data", "data-raw", "GODAD.csv.zip"), "projectlevel_china_wb.csv" ) ) world <- ne_countries(scale = 110, type = "map_units") |> filter(admin != "Antarctica") projects <- project_level |> st_as_sf(coords = c("longitude", "latitude"), crs = st_crs("EPSG:4326")) ggplot() + geom_sf(data = world) + geom_sf(data = projects, size = 0.01, alpha = 0.05) + theme_void() A world map of foreign aid projects
April 18, 2025 at 6:45 PM
Reposted by sayuks
aecoppock.bsky.social
New visualization tool alert!

The vayr package version 1.0.0 is now on CRAN.

It contains position adjustments for ggplot2 that help with overplotting in pleasing ways. My favorite is position_sunflower().

- install.packages("vayr")
- alexandercoppock.com/vayr

#rstats #ggplot2 #dataviz
position_jitter() position_jitter_ellipse() position_sunflower() position_circlepack()
April 16, 2025 at 7:53 PM
sayuks.bsky.social
I created an R package that makes it easy to create Tabsets in Quarto.
sayuks.github.io/quartabs/

#rstats #quarto
quartabs
sayuks.github.io
March 15, 2025 at 7:20 AM
Reposted by sayuks
njtierney.bsky.social
I mostly structure new projects as targets - code that get reused gets spun into a pkg.

The targets structure looks like Miles’s {tflow} design: github.com/njtierney/de...

At the other end of complexity, here are 2 larger projects:

github.com/njtierney/tt...

And

github.com/idem-lab/map...
GitHub - njtierney/demo-geotargets
Contribute to njtierney/demo-geotargets development by creating an account on GitHub.
github.com
March 5, 2025 at 10:33 AM
Reposted by sayuks
hadley.nz
What advice do folks have for organising projects that will be deployed to production? How do you organise your directories? What do you do if you're deploying multiple "things" (e.g. an app and an api) from the same project?
February 27, 2025 at 2:15 PM
Reposted by sayuks
nrennie.bsky.social
Now updated with more resources, and the ability to search and filter by different categories!

Link: nrennie.rbind.io/data-science...

#RStats #DataScience
Screenshot of data science resources website with a drop down menu for type, and search boxes for other columns.
November 1, 2024 at 6:23 PM