flor14/learning_R

Sources to learn R!

learning_R

R Programming

• CRAN Contributed Documentation https://cran.r-project.org/

Books

• Repository: Books about R programming. https://github.com/RomanTsegelskyi/rbooks
• R Programming for Data Science Roger D. Peng 2016-12-22 http://bit.ly/2AbQRhd
• R for Data Science Garrett Grolemund & Hadley Wickham http://bit.ly/2AaFWEw
• Efficient R programming Colin Gillespie & Robin Lovelace http://bit.ly/2AaGKcw
• Advanced R Hadley Wickham http://bit.ly/2AapVhT
• El arte de programar en R Julio Sergio Santana & Efraín Mateos Farfán [español] http://bit.ly/2N2Y1Y8
• Wikibook R Programming https://en.wikibooks.org/wiki/R_Programming
• Modern Dive. Chapter 2 Getting Started with Data in R https://moderndive.com/2-getting-started.html

String manipulation

• String Manipulation in R with stringr (Rpubs) https://rpubs.com/iPhuoc/stringr_manipulation
• Regular Expression in R Gloria Li and Jenny Bryan http://stat545.com/block022_regular-expression.html

Rstudio

Webinars

• Programming - Part 1 (Writing code in RStudio) http://bit.ly/2AaZ4Cf

• Programming - Part 2 ((Debugging code in RStudio) http://bit.ly/2AaifvV

• Programming - Part 3 (Package writing in RStudio) http://bit.ly/2AayPfq

• Managing - Part 1 (Projects in RStudio) http://bit.ly/2Abo3We

• Managing - Part 2 (Github and RStudio) http://bit.ly/2A9Pu2D

• Managing - Part 3 (Packrat and RStudio) http://bit.ly/2AazLAs

• Debugging techniques in RStudio Amanda Gadrow [video] http://bit.ly/2QQD4C2

• RStudio IDE https://frahik.github.io/DiplomadoR/RStudio.html

tidyr and dplyr Packages

• Tidy evaluation is one of the major feature of the latest versions of dplyr and tidyr [Video] http://bit.ly/2AbXJLs
• Tidy eval: Programming with dplyr, tidyr, and ggplot2 Hadley Wickham [Video] http://bit.ly/2QR07N5
• Tidyevaluation UseR! 2019
• Data wrangling with R and RStudio [Video] http://bit.ly/2AaocZX slides: http://bit.ly/2QSr7vS
• dplyr tutorials Suzan Baert http://bit.ly/2AbSHi2
• dplyr 10 tips and tricks Suzan Baert (RoCur WeAreRLadies) http://bit.ly/2AaWb4k
• STAT 545 Course Jenny Bryan http://bit.ly/2AajX0o
• Join Functions Jenny Bryan http://bit.ly/2AbUZ0C
• Let the Data Flow: Pipelines in R with dplyr and magrittr http://bit.ly/2AaVDvz
• Data Processing with dplyr & tidyr (Rpubs) http://bit.ly/2Aah7Zd
• Introducción a tidyr: Datos ordenados en R (Rpubs) [español] http://bit.ly/2AaWV9T
• dplyr Rstudio cheatsheet http://bit.ly/2IEwRcM
• Suzan blog con tutorial de dplyr en 3 partes https://suzan.rbind.io/2018/02/dplyr-tutorial-3/

data.table Package

• Intro to data.table Package http://bit.ly/2Aa6Yf3
• Wrangling with data.table http://bit.ly/2QQfLIy
• R studio cheatsheet (data.table) http://bit.ly/2IEwRcM
• Data crunching with data.table (Rpubs) http://bit.ly/2AbNCGz

ggplot2 Package

• DataCarpentry resources: http://bit.ly/2Aaiwz2
• Visualización estática e interactiva con ggplot2 y plotly [español] http://bit.ly/2xI2dqH
• Data Visualization in R http://bit.ly/2AaKzy9
• R graphics with ggplot2 workshop notes http://bit.ly/2AavgG4
• Data visualization using ggplot2 http://bit.ly/2Aal7ZT
• ggplot2 package by Hadley Wickham (Rpubs) http://bit.ly/2AaaeqN
• 7 Visualizations You Should Learn in R http://bit.ly/2NwhCBf
• How to make fancy graphs with ggplot2 (Medium post) http://bit.ly/2PTV51W
• Create BBC style graphics BBC https://bbc.github.io/rcookbook/#how_to_create_bbc_style_graphics

Books

• Data Visualization A practical introduction Kieran Healy http://bit.ly/2AaF9n2
• Data Visualization with R. Rob Kabacoff http://bit.ly/2A9pLaj

Shiny Web Application

• Rstudio Resources http://bit.ly/2QOovPq
• Building Web Applications in R with Shiny (Datacamp FREE COURSE) http://bit.ly/2QPEyN2
• Introduction to Shiny [video] http://bit.ly/2Aat9BQ
• Testing Shiny applications with Shinytest - Shiny developers now have tools for automated testing of complete applications [video] http://bit.ly/2AauJUq
• Understanding PCA using Shiny and Stack Overflow data Julia Silge [video] http://bit.ly/2QLmG5K
• Developing and deploying large scale Shiny applications Herman Sontrop [video] http://bit.ly/2QT8rMx
• Understanding Shiny Modules [video] http://bit.ly/2AaTuzS
• Interactive Graphics with Shiny [video] http://bit.ly/2Aau45h
• Building big Shiny Apps Colin Fay https://thinkr-open.github.io/building-shiny-apps-workflow/golem.html
• ShinyProxy y links a otros posteos sobre deploy https://www.databentobox.com/2020/05/31/shinyproxy-with-docker-swarm/?fbclid=IwAR1EaMVe5v3iAz9MyC8SxTjUx6bGGgWY3F6eTme24OA-k9lRKwA4mtq6VxA
• SHINY APP DATA VIS https://nshrest.shinyapps.io/datawhats/

Shiny deploy

• shinyapps.io https://docs.rstudio.com/shinyapps.io/index.html
• Data storage shiny app https://shiny.rstudio.com/articles/persistent-data-storage.html#local-vs-remote
• Deploying with googlesheets4 https://medium.com/@JosiahParry/googlesheets4-authentication-for-deployment-9e994b4c81d6

Interative plots

• Interactive web-based data visualization with R, plotly, and shiny Carson Sievert https://plotly-r.com/index.html
• Dash for R users https://dashr.plotly.com/

R Markdown

• R Markdown Gallery http://bit.ly/2QPHxoI
• R Markdown articles http://bit.ly/2A9LfEe
• R Markdown Rstudio lessons http://bit.ly/2A9Ln6G
• R Markdown and knitr make it easy to intermingle code and text to generate compelling reports and presentations that are never out of date. [video] http://bit.ly/2A9MH9E
• Beyond static reports with R Markdown [video] http://bit.ly/2Ac2jtd
• Introducing Notebooks with R Markdown [video] http://bit.ly/2AaYPXH
• Pimp my Rmd https://holtzy.github.io/Pimp-my-rmd/
• Embed files https://yihui.name/en/2018/07/embed-file/ - https://stackoverflow.com/questions/54072480/how-to-includeand-display-multiple-page-pdf-in-r-markdown-html-file
• slickR https://metrumresearchgroup.github.io/slickR/
• Writing academic papers https://daijiang.name/en/2017/04/05/writing-academic-papers-with-rmarkdown/

Books

• R Markdown: The Definitive Guide Yihui Xie, J. J. Allaire, Garrett Grolemund http://bit.ly/2QNTISX

Bookdown & Blogdown

• Introducing bookdown [video] http://bit.ly/2AbArpc
• Introducing blogdown, a new R package to make blogs and websites with R Markdown [video] http://bit.ly/2AamVSt
• Posts about HUGO and blogdown. Alison Hill blog https://alison.rbind.io/post/

Books

• bookdown: Authoring Books and Technical Documents with R Markdown Yihui Xie http://bit.ly/2QLTZWq
• blogdown: Creating Websites with R Markdown Yihui Xie, Amber Thomas, Alison Presmanes Hill http://bit.ly/2QPjCpm

R Package Development

• Write your first R Package (STAT 545 Course) Jenny Bryan http://bit.ly/2OjiBs2
• You can make a package in 20 minutes Jim Hester [Video] http://bit.ly/2QR3K5D
• What makes a great R package? Joseph Rickert [Video] http://bit.ly/2QLS9Vw
• How to develop good R packages (for open science) Maëlle Salmon http://bit.ly/2QTXgmP
• Writing an R package from scratch (Not so Standard deviations blogpost) Hilary Parker http://bit.ly/2QOlONO
• R Package Development Pictorial http://bit.ly/2QP5tbW
• Developing Packages with RStudio http://bit.ly/2QOav8v
• Writing an R package from scratch http://bit.ly/2QTWZAj
• Reproducible Research: Writing an R Package. http://bit.ly/2AarXi0
• Advanced R Course (Chapter 6: R Packages) Florian Privé http://bit.ly/2QT53kN

Documenting packages

• Roxygen2 https://kbroman.org/pkg_primer/pages/docs.html
• Formatting Roxygen2 https://cran.r-project.org/web/packages/roxygen2/vignettes/formatting.html

Books

• R Packages Hadley Wickham http://r-pkgs.had.co.nz/

purrr Package

• Happy R Users Purrr – Tutorial Charlotte Wickham [Video] http://bit.ly/2AakkIv
• Purr tutorial - Charlotte Wickham http://bit.ly/2AaDCNO
• Purr tutorial - Jenny Bryan http://bit.ly/2QSVoLC

How to write functions in R.

• Jenny Bryan's STAT 545 Course http://bit.ly/2QGCtnc

R-Spatial

• Spatial Data Analysis and Modeling with R http://rspatial.org/
• Geocomputation with R Robin Lovelace, Jakub Nowosad, Jannes Muenchow http://bit.ly/2TzxMwU
• Spatial modelling using ‘raster’ package (useR! Conf 2018) - [Part 1] http://bit.ly/2SJ9PTB [Part 2] http://bit.ly/2SIJgOr
• Layouts https://www.r-spatial.org/r/2018/10/25/ggplot2-sf-3.html
• An Introduction to Spatial Data Analysis and Visualisation in R _Guy Lansley and James Cheshire_https://data.cdrc.ac.uk/tutorial/an-introduction-to-spatial-data-analysis-and-visualisation-in-r
• Datos geoespaciales en español - Victor Olaya: https://t.co/LGXktkibl6?amp=1
• Raster operations in R https://mgimond.github.io/Spatial/raster-operations-in-r.html

Reproducible Research & Open Science

• Best Practices for Scientific Computing Greg Wilson … Paul Wilson | PLoS Biology 2014 https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745
• Archiving a Research Project Website on Zenodo. Opening Reproducible Research. https://o2r.info/2019/02/24/archiving-jekyll-zenodo/
• Open research software and open source. Eliademy. https://eliademy.com/catalog/oer/module-5-open-research-software-and-open-source.html
• Writing articles and reproducible documents R Anna Quagleri https://rpubs.com/annaquagli/471405
• Research Software The Carpentries https://librarycarpentry.org/Top-10-FAIR/2018/12/01/research-software/
• Transparent and Reproducible Research with R University of Oregon https://github.com/ResearchTransparency/rr_aera19/blob/master/README.md
• Challenges in irreproducible research Nature https://www.nature.com/collections/prbfkwmwvz/
• Oh shit Git! https://ohshitgit.com/
• Git for humans Alice Bartlett https://speakerdeck.com/alicebartlett/git-for-humans
• Open Science: sharing your research with the world https://www.edx.org/course/open-science-sharing-your-research-with-the-world-2
• The Practice of Reproducible Research. Case Studies and Lessons from the Data-Intensive Sciences. Justin Kitzes, Daniel Turek, Fatma Deniz https://www.practicereproducibleresearch.org/
• netoma package Building your network using ORCID number https://downwithtime.wordpress.com/2015/02/12/building-your-network-using-orcid-and-ropensci/
• workflowr package for researchers https://github.com/jdblischak/workflowr
• Making your code citable github https://guides.github.com/activities/citable-code/
• Reproducible Science Curriculum https://github.com/Reproducible-Science-Curriculum
• RMarkdown for Scientists Nicholas Tierney https://rmd4sci.njtierney.com/why-rmarkdown.html#overview
• Research Compendium https://research-compendium.science/
• paper - mas impacto si se puede dejar libre https://peerj.com/articles/3208/?utm_source=TrendMD&utm_campaign=PeerJ_TrendMD_0&utm_medium=TrendMD
• https://www.practicereproducibleresearch.org
• Git cheatcheet https://github.github.com/training-kit/downloads/es_ES/github-git-cheat-sheet/
• "A Guide to Reproducible Code in Ecology & Evolution" @BritishEcolSoc https://buff.ly/2HXsOWI
• Anna's slides about reproducible science with R https://annakrystalli.me/talks/r-in-repro-research.html#1
• Binder rstudio ide https://github.com/binder-examples/r_with_python
• renv reemplace of packrat https://blog.rstudio.com/2019/11/06/renv-project-environments-for-r/
• checkpoint - Install Packages from Snapshots on the Checkpoint Server for Reproducibility https://github.com/RevolutionAnalytics/checkpoint
• Mine slides
• A Realistic Guide to Making Data Available Alongside Code to Improve Reproducibility. Nicholas J Tierney* (1,2) & Karthik Ram* (3) https://github.com/karthik/ddd
• Software and workflow development practices (April 2020 update) Titus Brown http://ivory.idyll.org/blog/2020-software-and-workflow-dev-practices.html
• Nüst, D., Sochat, V., Marwick, B., Eglen, S., Head, T., Hirst, T., & Evans, B. (2020, April 17). Ten Simple Rules for Writing Dockerfiles for Reproducible Data Science. https://doi.org/10.31219/osf.io/fsd7t
• Kitzes, J., Turek, D., & Deniz, F. (Eds.). (2018). The Practice of Reproducible Research: Case Studies and Lessons from the Data-Intensive Sciences. Oakland, CA: University of California Press. https://www.practicereproducibleresearch.org/case-studies/dsinghania.html

ReproHack

• Find out research reproducibility https://scigen.report/
• The Turing Way https://www.turing.ac.uk/research/research-projects/turing-way-handbook-reproducible-data-science
• ReScience C is an open-access peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research is reproducible http://rescience.github.io/
• DRAKE package https://ropenscilabs.github.io/drake-manual/index.html#why-drake
• Nusch - How to Read a Research Compendium https://arxiv.org/pdf/1806.09525.pdf
• rrtools tutorial anna krystalli https://annakrystalli.me/rrtools-repro-research/paper.html
• codecheck https://codecheck.org.uk/

Replicate papers (databases)

• Social sciencies and economics https://replication.uni-goettingen.de/wiki/index.php/Main_Page?fbclid=IwAR2wATNeFvUIIwa0e0oiutoirThwt35MpwXvmdC16cpspOzxgUVqVdJzCZY
• Harvard Dataverse https://dataverse.harvard.edu/

Journals or pages related

• Reproducibility Project: Psychology https://osf.io/ezcuj/
• Curate Science https://curatescience.org/app/
• MIT - Citing & publishing software: Publishing research software https://libguides.mit.edu/c.php?g=551454&p=3786120#s-lg-box-wrapper-14235641+
• Journals for publishing software https://www.software.ac.uk/which-journals-should-i-publish-my-software

Statistics with R

• Open Intro https://www.openintro.org/
• Courses in Statistics https://www.coursera.org/instructor/minecetinkayarundel
• Estadistica Computacional https://tereom.github.io/est-computacional-2018/
• Learning statistics with R https://learningstatisticswithr.com/book/
• https://allisonhorst.shinyapps.io/missingexplorer/
• https://brandonhoenig.shinyapps.io/IntroToR/
• https://cal-poly-advanced-r.github.io/STAT-431/
• https://datavizm20.classes.andrewheiss.com/
• https://bookdown.org/ansellbr/WEHI_tidyR_course_book/
• https://github.com/mattansb/Advanced-Research-Methods-foR-Psychologists/tree/1.0.0
• https://github.com/adw96/biostat561/
• https://www.infoworld.com/video/series/8563/do-more-with-r

Tidyverse

• Welcome to the tidyverse https://joss.theoj.org/papers/10.21105/joss.01686

Multivariado

• Introduction to statistical learning de Hastie y Tibshirani https://www-bcf.usc.edu/~gareth/ISL/ISLR%20First%20Printing.pdf
• Análisis de datos multivariantes Peña https://www.researchgate.net/publication/40944325_Analisis_de_Datos_Multivariantes
• Nuevos métodos de análisis multivariante Cuadras http://www.ub.edu/stat/personal/cuadras/metodos.pdf
• Diferencia entre algoritmos de clustering https://nbviewer.jupyter.org/github/lmcinnes/hdbscan/blob/master/notebooks/Comparing%20Clustering%20Algorithms.ipynb

Data Science

• Elements and Principles of Data Analysis Hicks SC, Peng RD https://arxiv.org/abs/1903.07639
• Evaluating the Success of a Data Analysis Hicks SC, Peng RD https://arxiv.org/abs/1904.11907
• AWS training and certification https://aws.amazon.com/es/training/learning-paths/machine-learning/data-scientist/
• Introduction to Open Data Science The Ocean Health Index Team http://ohi-science.org/data-science-training/index.html
• https://stat545.com/index.html

Programación / data science en español

• Ciencia de datos para curiosos Martín Montané https://bookdown.org/martinmontaneb/CienciaDeDatos/
• Fundamentos de la Programación Estadística y Data Science en R - Versión tidyverse German Rosati https://github.com/gefero/tidy_fund_prog_r
• Ciencia de datos para gente sociable Vazquez Brust https://bitsandbricks.github.io/ciencia_de_datos_gente_sociable/
• El arte de programar en R Julio Sergio Santana & Efraín Mateos Farfán [español] http://bit.ly/2N2Y1Y8
• Introducción a tidyr: Datos ordenados en R (Rpubs) [español] http://bit.ly/2AaWV9T
• Visualización estática e interactiva con ggplot2 y plotly [español] http://bit.ly/2xI2dqH
• Curso de R para procesamiento de datos de la Encuesta Permanente de Hogares Diego y Natsu https://diegokoz.github.io/Curso_R_EPH_clases/

RSE

• https://imperialcollegelondon.github.io/grad_school_software_engineering_course/

Biology and Environmental Sciences

• Modern Statistics for Modern Biology Holmes, S and Huber, W https://www.huber.embl.de/msmb/
• The R class R programming for biologists http://r-bio.github.io/01-intro-R/
• Seascape models. Resources to solve environmental problems. http://www.seascapemodels.org/code.html
• Resources for Taxonomy and Biodiversity. ROpenSci. https://ropensci.org/blog/2019/03/11/commcall-mar2019/
• Bioinformatics Bernard Klaus https://www.huber.embl.de/users/klaus/teaching.html#statistical-methods-in-bioinformatics
• Data carpentry for Biologists https://datacarpentry.org/semester-biology/nav/getting-started/
• DATA SCIENCE FOR ECOLOGISTS AND ENVIRONMENTAL SCIENTISTS https://ourcodingclub.github.io/course.html?fbclid=IwAR1M5xhRXmdXH5EsIExLabpIK1llb8AOQ2n0qncSvkVE3JUYDuveXijk9EM

Docker for the UseR

• Docker for the UseR Noam Ross https://github.com/noamross/nyhackr-docker-talk
• An inroduction to Docker for R users Colin Fay https://colinfay.me/docker-r-reproducibility/
• Docker Documentation https://docs.docker.com/
• Docker for begginers Prakhar Srivastav https://docker-curriculum.com/#what-is-docker-
• Dockerize a shinyapp https://www.bjoern-hartmann.de/post/learn-how-to-dockerize-a-shinyapp-in-7-steps/
• A Docker tutorial for reproducible research. http://ropenscilabs.github.io/r-docker-tutorial/
• List of R versions available in Docker. https://hub.docker.com/r/rocker/r-ver/tags/
• docknitr: Use Docker Images to Process Rmarkdown Blocks https://cran.r-project.org/web/packages/docknitr/index.html
• Nature: cloud services https://www.nature.com/articles/d41586-019-03366-x?utm_source=twitter&utm_medium=social&utm_campaign=crs-&utm_content=171119v1
• Leccion carpentries https://carpentries-incubator.github.io/docker-introduction/

Testing

• Software Quality - TDD and unit testing in R using the 'testthat' package https://pparacch.github.io/2017/05/18/test_driven_development_in_r.html
• Webinars TDD Hernán Wilkinson https://university.10pines.com/webinars_and_videos
• testthat: Get Started with Testing Hadley Wickham https://journal.r-project.org/archive/2011-1/RJournal_2011-1_Wickham.pdf
• PACKAGES FOR TESTING YOUR R PACKAGE maelle https://itsalocke.com/blog/packages-for-testing-your-r-package/

Continuos integration

• A BEGINNER'S GUIDE TO TRAVIS-CI FOR R Julia Silge https://juliasilge.com/blog/beginners-guide-to-travis/
• Charla de Jim Hester sobre github actions

Tutorials / different topics

• Learning Javascript https://github.com/P1xt/p1xt-guides/blob/master/job-ready-javascript-edition-3.0.md
• The coding club https://ourcodingclub.github.io/tutorials/
• Javascript vs Data science https://software-tools-in-javascript.github.io/js-vs-ds/en/
• Tutorial: build a blog with Jekyll and GitHub pages https://www.smashingmagazine.com/2014/08/build-blog-jekyll-github-pages/
• Tutorials for multiple programming languajes by Mike Dane https://www.mikedane.com/
• https://databasic.io/es/
• Template online course starter: R https://github.com/ines/course-starter-r

Tutorials

• Chromebook Data Science https://jhudatascience.org/chromebookdatascience/
• Swirl. Learn R in R https://swirlstats.com/

R base

• Diferencia entre rank, sort y order https://towardsdatascience.com/r-rank-vs-order-753cc7665951

Blog

• https://makingwebsiteswithr.rbind.io/tutorial/01-install-blogdown/

Extra: Virtual meetings

• Slack https://jitsi.org/slack/
• Without installing https://whereby.com/
• Zoom
• https://meet.google.com

Extra: online meetups (teaching online) Contributed by several R-Ladies - see gdoc

• https://codeocean.com/ code with others
• https://twitter.com/CivicAngela/status/1238481908633423873
• https://www.linkedin.com/pulse/virtual-meetups-noa-tamir/
• https://codebuddies.org/
• https://carpentries.org/blog/2020/03/tips-for-teaching-online/
• https://github.com/alan-turing-institute/the-turing-way/blob/ms-collaboration-book/book/content/remote_collaboration/checklist/checklist.md#during-the-event
• https://codeshare.io/
• https://coronavirustechhandbook.com/education
• https://docs.google.com/document/d/1ZXmwVibQKtfCY_HiB49-OhQL-yKhUS9YD9yeMQZH88E/edit?usp=sharing (satRday Neuchâtel)
• https://help.meetup.com/hc/en-us/articles/360041040931
• https://help.meetup.com/hc/en-us/articles/360040609112
• AUDIO CALLS https://www.mumble.com/
• Share code online https://twitter.com/code

Otros blogs de interes

• What Every Programmer Absolutely, Positively Needs To Know About Encodings And Character Sets To Work With Text https://kunststube.net/encoding/

Extra: subtitles

• Amara https://amara.org/

Education

• Repo https://github.com/flor14/educacion_teaching

Extra: online events

• https://carpentries.org/online-workshop-recommendations/
• https://bookwhen.com/betteronlinemeetings
• https://carpentries.org/blog/2020/04/plan-map-live-coding-workshop/
• Jumping into digital lessons https://www.youtube.com/watch?v=w0DHye2M1IM

Extra: Podcasts

• Credibly Curious is about R: https://soundcloud.com/crediblycurious
• Not so standard deviations: http://nssdeviations.com/
• The corresponding author: Academic Data Science https://twitter.com/CorrespondAuth (editado)
• Casual Infer: http://casualinfer.libsyn.com/
• R podcast: https://r-podcast.org/r

Extra: Free events

• Simil meetup but free https://attending.io/

Extra: Slides

• https://speakerdeck.com/
• https://slides.com/

Extra: R events worldwide

• List of events https://jumpingrivers.github.io/meetingsR/events.html
• Attend to a conference https://gist.github.com/tatianamac/493ca668ee7f7c07a5b282f6d9132552
• Guia de eventos de R https://unconf-toolbox.github.io/unconf-guide/index.html

Others

• Toolkit https://toolkits.dss.cloud/design/
• Collaborative Markdown notes https://hackmd.io
• The Carpentries Pad https://pad.carpentries.org
• CARBON Beautiful code chuncks http://bit.ly/30Mmatt
• MathJax for browsers https://www.mathjax.org/
• Listas de correo https://tinyletter.com/
• How to use Zotero https://ikashnitsky.github.io/2019/zotero/
• Undestanding the R help Kieran Healy https://socviz.co/
• Lista de blogs contribuidas https://awesome-blogdown.com/
• Guía de traducción al inglés https://github.com/cienciadedatos/documentacion-traduccion-r4ds/blob/master/orientaciones-traduccion.md
• Como resolver entrevistas https://www.youtube.com/watch?v=Csl2ccBpo4g&feature=youtu.be

Extra: genero

• Guia de escritura con perspectiva de genero https://www.argentina.gob.ar/sites/default/files/guia_para_una_comunicacion_con_perspectiva_de_genero_-_mmgyd_y_presidencia_de_la_nacion.pdf