#rstats

Liam Revell (@phytools_liam; ¹⁰⁵⁷⁄₁₃₀): That’s a real, physical book, people. @lukejharmon #Rstats https://t.co/z0IMsz2QVX https://t.co/VE28O3aFUQ ↪

Gilbert Fontana (@GilbertFontana; ⁵⁶²⁄₁₃₁): Interest rates over the last 150 years > Code: https://t.co/pphNy2Rmuf > #RStats #ggplot2 #ggplot #Datavisualization #dataviz #datadesign #DataScience #DataDriven #Visualization https://t.co/dzI5Irvkp1 ↪

Matt Dancho (Business Science) (@mdancho84; ⁵⁰¹⁄₁₀₁): Machine learning is great, until you have to explain it. > Don’t worry. This R package will save you. > https://t.co/hurpZoiu2n > #rstats https://t.co/mJ98iPL6eU ↪

Matt Dancho (Business Science) (@mdancho84; ³⁶⁶⁄₅₁): A new #R package that makes it easy to edit data in R. > Article: https://t.co/K4mL7yPMrr > #rstats #datascience https://t.co/ZX5NaSZ8OW ↪

Mikhail Popov (@bearloga; ³⁶⁰⁄₃₈): I love R because I needed to extract some slides as PNGs out of a slide deck PDF and it was almost effortless. #RStats https://t.co/b8rFmPecAn ↪

David Granjon (@divadnojnarg; ³⁴²⁄₆₆): Hi #RStats. You like {shinydashboard} but want to quickly customize some elements … or you would like to seamlessly import that amazing material bootstrap box into vanilla shiny? Chapter 2 and 4 of Outstanding user Interfaces with Shiny deep dive into {htmltools} (¹⁄₃) https://t.co/WLu7f7JwOl ↪

Barret Schloerke (@schloerke; ³⁴¹⁄₅₇): I’d like to announce 📢 two new ✨ #rstats packages to CRAN: * {chromote} - Headless Chrome Remote Interface * {webshot2} - Take screenshots of web pages from R ↪

Annapurani (@annapurani93; ²⁶⁰⁄₅₂): If you’re looking to navigate the universe of #RStats, here are some packages - on data import, wrangling, visualization and analysis - that you should definitely toss into your bag. Check them out! > #DataScience #tidyverse #ggplot2 https://t.co/bQvfRPELjy ↪

Mena Ning WANG, PhD (@mena_wang; ²¹⁵⁄₂₇): Want to add statistical test results to a plot? > add_pval() function in {ggpval}📦performs the desired statistical test between groups and adds the corresponding p-values to ggplots. > Works well with various geoms (e.g., bar, boxplot) and on faceted plots too. > #rstats #DataViz https://t.co/kU3UDb908N ↪

Milos Popovic (@milos_agathon; ¹⁹⁵⁄₅₀): In my latest map, I mapped the net migration rate (population change not attributable to births and deaths) in Europe. > #migration #maps #RStats #DataScience #dataviz #rspatial https://t.co/lRlG7deu79 ↪

Pachá (@pachadotdev; ¹⁹³⁄₃₇): leaRn! (learn R) * All levels * No prior experience required * Certified RStudio Trainer (Tidyverse + Shiny) * Also certified by The Carpentries at UofT * Eight years of experience with R and databases See my email in the image #rstats https://t.co/2RbykZ7BHx ↪

Dr. Ganapathi Pulipaka 🇺🇸 (@gp_pulipaka; ¹⁵²⁄₇₄): 100+ Free Machine Learning eBooks. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
https://t.co/3Wx8H7FlPu https://t.co/N3L78ZpKBu ↪

Tanjila #Smm (@Tanjilasmm; ¹⁴¹⁄₈₀): Why Are We Teaching #Pandas Instead of #SQL? > #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #DataScientist #Linux #Coding #100DaysofCode #pythoncode #Python #Data https://t.co/hzKXVFKHHp ↪

Dr. Ganapathi Pulipaka 🇺🇸 (@gp_pulipaka; ¹³⁵⁄₈₉): #DevOps Roadmap - A Deep Dive into #DevOps Roadmap. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
https://t.co/jUm8aIY0Ku https://t.co/VHblyXvyFs ↪

Syeda Sheraj Ali (@Sheraj99; ¹²⁵⁄₉₆): #DevOps Roadmap - A Deep Dive into #DevOps Roadmap. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
https://t.co/H3fTYE02yz https://t.co/YzrpWWS2Uo ↪

blogdown

Yanina Bellini Saibene (@yabellini; ²⁸⁄₁₇): En @_useRconf 2022 tenemos varios tutoriales en español: > 💻”Creación y publicación de un blog estadístico con el paquete {blogdown}” por @emilopezcano de @R_Hisp > 🛠️ “Introducción al aprendizaje automático responsable” por Juan Correa ¹⁄₃ ↪

Pao Corrales (@PaobCorrales; ¹⁰⁄₁): Actualicé mi web usando Hugo Apero, que fruta noble blogdown. > https://t.co/us6ClBJlN4 ↪

Mine Çetinkaya-Rundel (@minebocek; ⁷⁄₁): @jtrnyc At the risk of giving an answer you didn’t ask for: https://t.co/8fCOhUJykk. > But if you already know those tools and don’t feel like trying out something new, I think I’d use blogdown b/c I feel like there are more comprehensive, easier to follow (for me) tutorials/docs for it. ↪

Ewan Donnachie (@ERDonnachie; ³⁄₂): @DavidBo28287340 @rstats_tweets Within the rmarkdown family (bookdown, blogdown, distill etc), there are subtle differences in features and how they are implemented. Quarto promises to take the best of these packages and provide a more unified framework. > See also @xieyihui ’s blogpost: https://t.co/1lGIArwAPW ↪

Joyce Robbins (@jtrnyc; ²⁄₂): For creating a simple blog on GH pages w/ Hugo, which doesn’t have R code, would you use #blogdown or just use Hugo directly w/o #rstats? ↪

Michael Flynn (@flynnpolsci; ²⁄₀): Please excuse the embedded tweets not rendering properly. For whatever reason the version of blogdown/Hugo that I’m using doesn’t seem to be rendering them properly and I’m terrified to update because it’s a pain in the ass to figure out to how not break/unbreak things. ↪

Jason Geller (@jgeller_phd; ¹⁄₀): @EMBrains https://t.co/J9hOr0jEa6 ↪

AgencyReadyMarketing (@agency_ready; 0/3): Google Analytics does not work with blogdown – R #WebAnalytics #DigitalMarketing #GoogleAnalytics [Video] https://t.co/F8jZOw5Vko ↪

bookdown

秦の告知アカウント (@hata_kpu; ¹⁰⁄₁): Chapter 4 データの加工 | Rによる社会調査データ分析の手引き https://t.co/RozqBFtXHP #rmarkdown #bookdown > 麦山先生のこのwebページが一番参考になる。 ↪

Frederick Thielen (@FWThielen; ⁹⁄₃): Yesterday I presented 2 topics @rhta16 2022 workshop showing how to use the #rpackages #cbsodataR & #bookdown. Maybe a little too much ℹ️ for the short amount of ⏱ but all materials are on #github Slide layout partly inspired by work of @apreshill 🙏 > https://t.co/OSMZ1nuTSE ↪

Jaehyun Song (@Tintstyle; ⁹⁄₂): 個人ホームページのエンジンをbookdownからquartoへ変更しました。既存のURLのほとんどは使えませんが、資料自体は全て掲載されています。右上の虫眼鏡ボタンで検索してください。 > https://t.co/opjZ7xBV1B ↪

Espacio Muestral (@espaciomuestral; ⁷⁄₄): #TeRecomendamos 📚

𝗥𝗦𝘁𝘂𝗱𝗶𝗼 𝗽𝗮𝗿𝗮 𝗘𝘀𝘁𝗮𝗱𝗶́𝘀𝘁𝗶𝗰𝗮 𝗗𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝘃𝗮 𝗲𝗻 𝗖𝗶𝗲𝗻𝗰𝗶𝗮𝘀 𝗦𝗼𝗰𝗶𝗮𝗹𝗲𝘀 👇 • Librerías
• Estimaciones puntuales
• Inferencia • Gráficos • Markdown

https://t.co/yYJZi4kiFC ↪

Solomon Kurz (@SolomonKurz; ⁷⁄₀): @EikoFried MELSM: https://t.co/b3wLOhRfdj. ↪

Matt Peeples (@PattMeeples; ⁵⁄₀): Python and R-Studio deploying bookdown project from my phone. Kinda pointless but neat nonetheless. https://t.co/a5H8HqE0kF ↪

Javan Okendo (@javan_okendo; ³⁄₂): Computational Genomics with R is a good book . try is out @louis_okwaro https://t.co/QcJWlgkwO8 #rmarkdown #bookdown ↪

tipsder (@tipsder; ²⁄₂): ¡Ciencia de datos para curiosos! Libro web con un enfoque para el uso y aprendizaje de #R a través de la ciencia de los datos. https://t.co/bTrIuh4oaV #RStats #DataScientist #dataviz #Datavisualization #data ↪

Matt Crump (@MattCrumpLab; ²⁄₂): It’s written in #rmarkdown using #rstats tools like #pkgdown and #bookdown > I put some pointers about compiling everything yourself here (still bare bones, will add more tips soon) > https://t.co/2CJccm2wai ↪

Deepak Varughese, MD (@VarugheseDeepak; ¹⁄₁): @BalamoutKid @rstatstweet @rstudio Anything with r..... will be interpreted as code inline. https://t.co/Ez6kMEDGUg Not sure if that answers your question though. ↪

Gustave Courbet (@GustaveSchiller; ¹⁄₁): What is the harshest reason to use R Markdown, Bookdown, LaTeX et. al. for writing and publishing ? ↪

心理的に柔軟なクジラ (@matsuchiy; ¹⁄₀): bookdownでtipsとかの囲み作る方法やっと分かった。Callout blocksっていうのか。bs4_bookでのデフォルトは以下画像。カスタマイズの仕方はまだ分からぬ https://t.co/jUedU6z9kH https://t.co/DOiiW85DAD ↪

心理的に柔軟なクジラ (@matsuchiy; ¹⁄₀): Rによるテキスト分析のための教師あり機械学習 https://t.co/ZN70D6XvPk #bookdown ↪

Arthur Albuquerque (@arthur_alb1; ¹⁄₀): @TO_Rhino @EvidenceRobot @rstudio bookdown “Doing Meta-Analysis in R” ↪

Farong (@thundhaa; ¹⁄₀): @guerillacricket Damn rain… Where is my pdf bookdown ‘Converting your Rickshaw into a Canoe!’ Candle is ready for electricity to go out. Already occurred 3 times today. ↪

Jose M Ordonez-Mena (@JMOM85; ¹⁄₀): @dnunan79 @TrialBot How about using a statistical package? https://t.co/MfHRu1DIAP there are plenty of methods in R… I’m sure there is also a way using STATA/SPSS. ↪

Kyle Peyton (@pylekeyton; ¹⁄₀): @MattCowgill Seriously tho, I’ve spent a ton of time tweaking the “reference doc” so tables and column layouts look okay with some success, e.g. output: bookdown::word_document2: toc: yes fig_caption: yes reference_docx: “word-ref-01.docx” I’m sure you’e onto this already ↪

tidyverse tweets (@tidyversetweets; 0/1): Rendering flextables to pdf in bookdown/markdown do not fit to page #tidyverse #rstats https://t.co/HSDHl97CfW ↪

knitr

R Markdown (@rmarkdown; ¹⁴⁄₅): R Markdown Tips and Tricks #3: Time-savers & Trouble-shooters https://t.co/oH4QEDwGw9 #rmarkdown #rstats #knitr #rscript ↪

Sean Mackinnon (@seanpmackinnon; ¹¹⁄₀): @davidrfeinberg Use the sjPlot() package and > tab_model(model, file = “output.html”) > Then just copy paste from html into Word. > Not one click reproducibility, but close with least amount of steps, lots of saved time, and no fussing with knitR. ↪

Bruno Rodrigues (@brodriguesco; ⁴⁄₂): @theRcast @rweekly_org @ivelasq3 @_bcullen @apreshill @thomas_mock @mike_ketchbrook knitr_expand is crazy useful! I wrote a blog post on it last year, when I had to solve an issue that knitr_expand really made super simple https://t.co/mX3f1t1Z5t ↪

Michael T Young (@michaeltyoung3; ⁴⁄₀): @davidrfeinberg @rstatstweet knitr::kable(broom::tidy()) in an rmd document set to output to docx ↪

Michael Friendly (@datavisFriendly; ³⁄₃): #rstats #knitr #rmarkdown tip: If you use multiple BibTex databases and don’t want to copy these to the document folder, use system() to find them: > bibliography: - “r system('kpsewhich graphics.bib', intern=TRUE)“ - “r system('kpsewhich statistics.bib', intern=TRUE)” ↪

Zaeen de Souza (@zaeendesouza; ³⁄₁): knitr::purl() is an actual, legit lifesaver ↪

Bruno Rodrigues (@brodriguesco; ²⁄₀): @kaioinformatics I’ve made a knitr compile farm https://t.co/GMMAUqjaxw ↪

William Melo (W-Black) (@williamcorrearj; ²⁄₀): @CarolinaMedei12 E aí uma coisa q ajuda a deixar praticamente qq tabela bonita (caso inicialmente ela seja um data.frame) é usar %>% knitr::kable() %>% kableExtra::kable_styling(). Dentro dessa última tem um argumento chamado Bootstrap options, que te permite escolher vários estilos bonitos. ↪

rOpenSci (@rOpenSci; ¹⁄₂): [help wanted] rOpenSci 📦 tinkr is looking for some help! 🙏 > Check out the issue labelled ‘help wanted’ by @zkamvar: > “Add support for chunk options via knitr 1.35” at https://t.co/H0ZBoJo68Z > #RStats ↪

tidyverse tweets (@tidyversetweets; ¹⁄₁): grid.arrange and knitr graphic is not displayed in pdf #tidyverse #rstats https://t.co/1fWYs1Bauq ↪

Richard Meyer-Eppler (@r_meyereppler; ¹⁄₀): @brodriguesco @theRcast @rweekly_org @ivelasq3 @_bcullen @apreshill @thomas_mock @mike_ketchbrook It took me a while to realize that knit_expand is simply a generic text templating function, with no direct connection to knitr. You can just as easily use generic templating packages such as glue or brew, or even more specialized ones such as gluedown. ↪

xaringan

Hablamos R (@RHablamos; ⁵⁄₄): The basics of creating slides in RMarkdown using the Xaringan!!! package, pretty cool, I like it =) > #xaringan #rmarkdown #markdown #python #ggplot2 #100daysofcode #datascience #coding #programming #dataviz #datavisualization #rstudio #rstats #rstatsES > https://t.co/gdyH20gwVN ↪

Eric Brasil (@ericbrasiln; ³⁄₁): @BeaMilz @quarto_pub Que interessante! Eu estava procurando exatamente algo assim para fazer apresentações direto do VSCode (apesar de tb usar o Rmd e Xaringan lá). Vou testar o Quarto agora. ↪

Eric Brasil (@ericbrasiln; ²⁄₀): @BeaMilz @jimmy_medeiros @quarto_pub Vc acha mais interessante de Quarto ou de Rmarkdown + Xaringan? Me parece que o Quarto tem mais opções pra trabalhar com diferentes linguagens, o que pode ser uma vantagem. ↪

Beatriz Milz (@BeaMilz; ²⁄₀): @ericbrasiln @jimmy_medeiros @quarto_pub pensando no perfil do PH, acho que Quarto é interessante. Tem várias lições sobre Python por lá. O código de apresentações com quarto também é mais clean do que os de xaringan, na minha opinião. ↪

B.Martins (@brunomartolas; ¹⁄₀): Agora eu entendo um Uchiha vendo o Kakashi de xaringan ↪

Kenneth Fond (@kenf_1; ¹⁄₀): @DavidBo28287340 My experience with both: > Quarto pro: tweaks like figures side by side & html slides built in Quarto con: no templates (yet), still in beta > Rmarkdown pro: templates in packages + customizations, reliable Rmarkdown con: relies on other packages (xaringan…) ↪