R Weekly 2022-W37 Mapping wind, Expected points, LEGO model with Docker
This article is originally published at
Hello and welcome to this new issue!
This week’s release was curated by Jon Calder, with help from the R Weekly team members and contributors.
Highlight
Insights
R in the Real World
Calculating and comparing expected points from different expected goals sources (soccer)
Evaluating how we can use match outcome probabilites for season-long insights (soccer)
RObservations #38: Visualizing Average Delay Times On TTC Subway Stations
How strongly does German electricity demand react to high prices?
R in Academia
New Packages
CRAN
- {oceanexplorer} 0.0.1: Explore Our Planet’s Oceans with NOAA
{wordbankr} 1.0.0: Accessing the Wordbank Database
{luz} 0.3.1: Higher Level ‘API’ for torch
{NatParksPalettes} 0.1.4: Color Palettes Inspired by National Parks
GitHub
- {cropcircles} 0.1.0: Crop an Image into a Circle with a Transparent Background
Updated Packages
{telegram.bot} 3.0.0: Develop a ‘Telegram Bot’ with R - diffify
{officer} 0.4.4: Manipulation of Microsoft Word and PowerPoint Documents - diffify
{libr} 1.2.8: Libraries, Data Dictionaries, and a Data Step for R - diffify
{cli} 3.4.0: Helpers for Developing Command Line Interfaces - diffify
Videos and Podcasts
[TidyX Episode 115 R Classes and Objects - Making an S4 Object, Part 2 - S4 Tournament](https://www.youtube.com/watch?v=ktlJJHlR0Ck)
R Internationally
Tutorials
R Project Updates
Updates from R Core:
Upcoming Events in 3 Months
Events in 3 Months:
September 13: Fundamentals of Exploratory and Inferential Spatial Data Analysis in R workshop
September 14: ‘Advanced Shiny Development’ the hands-on workshop
September 21: R-Ladies NYC Lightning Talks - RSVP and Call for Speakers
October 6-7: Shiny in Production conference from Jumping Rivers
Grants & Funding
- R Consortium ISC Call for Proposals - Infrastructure Steering Committee (ISC) grants for low-to-medium risk projects with a focused scope and likely to have a broad impact on the R Community. Deadline 2022-10-01.
Datasets
{m5} 0.1.1: ‘M5 Forecasting’ Challenges Data
{allhomes} 0.3.0: Extract Past Sales Data from Allhomes.com.au
{BFS} 0.4.3: Get Data from the Swiss Statistical Office
{resampledata3} 1.0: Data Sets for “Mathematical Statistics with Resampling and R” (3rd Ed)
Jobs
💼 Explore Jobs & Gigs Board on RStudio Community 💼
rtistry
Shortly after I made a plot in June, I wrote a little Shiny app to experiment with different settings. And then added a theme and some buttons. Here it is, if you want to play with it:https://t.co/YP5Yq9SDsq#RStats #rtistry https://t.co/ZBUjKGWbje pic.twitter.com/b6AWRrl4BN
— Georgios Karamanis (@geokaramanis) September 9, 2022
Quotes of the Week
I've just discovered you can join, split, and compress PDF files with {pdftools} in #rstats, and extracted a specific chapter from a >3000 pages long PDF in two lines of code.
— Silvia Gutiérrez (@espejolento) September 5, 2022
I love you @rOpenSci
💻🤖💜
Code: https://t.co/xWP4JLXJHa pic.twitter.com/KvHdVtQVIo
I am teaching grad #DataVisualization this fall, so I want to know what you find HARD with data viz, both in general and specifically within #rstats & #tidyverse
— Dr. Emorie Beck (@EmorieBeck) September 6, 2022
Plz RT! I hope to make all these materials #openscience and will eventually couple it with a data management course!
My new favorite R package for uncovering distributions.
— Matt Dancho (Business Science) (@mdancho84) September 9, 2022
And I made a free tutorial to help you get up to speed. #rstats https://t.co/DdyySc3ksh pic.twitter.com/9ao7ZuAt8m
Thanks for visiting r-craft.org
This article is originally published at
Please visit source website for post related comments.