R Weekly 2020-09 ggplot2 Tutorials, R + Docker, Finding Causation

02 Mar 2020

Highlight

• A curated list of awesome ggplot2 tutorials, packages etc.

• A few examples of how you can use R & Docker for data science, from running a simple script to making reports with RMarkdown with a command line interface.

• Use regression, inverse probability weighting, and matching to close confounding backdoors and find causation in observational data

R in the Real World

• A few examples of how you can use R & Docker for data science, from running a simple script to making reports with RMarkdown with a command line interface.

An extremely thorough introduction into a difficult but valuable technique to learn

• BMI has an expectations management problem

• The significance of the sector on the salary in Sweden, a comparison between different occupational groups, part 2

• Book slides - Analyzing Financial and Economic Data with R

• Dealing with pressure(s) (FA Women’s Super League data)

R in Organizations

• What does your ‘Minimally Viable Data Scientist’ look like?

• Data Science Radar: How to Identify World-Class Data Science Capabilities

A two-part post that I found helpful in stating clearly what nebulous data-science-esque job ads are asking for

Videos and Podcasts

• 102 - Readable Tech Debt

• Quick Notes on Some rstudio::conf(2020) Talks after I Watched the Videos

• MLOPS for R with Azure Machine Learning

Insights

• R is turning 20 years old next Saturday. Here is how much bigger, stronger and faster it got over the years

Coming up to the 4th anniversary of using R, I enjoy reading about the history of the language that I did not experience. This post does this well, balancing the changes in the language itself, and the usage of R over the past 20 years since its 1.0.0 release

• R Robustreg Package Downloads

• You CRAN Do It

• 3 recommended books on learning R

• My First Uncoast Unconference in 2019

• Developing a complex R Shiny app – the good, the bad and the ugly

Most blogs on RWeekly so the development of code towards a final goal so I enjoyed this one that mostly focused on the human side of building a Shiny app. As a result, the app itself also seems extremely well designed for human users

R in Academia

• chain of lynx and drove of hares

• Peña, D., Smucler, E., & Yohai, V. (2020). gdpc: An R Package for Generalized Dynamic Principal Components. Journal of Statistical Software, 92(Code Snippet 2), 1 - 23. doi:http://dx.doi.org/10.18637/jss.v092.c02

• Dahl, D. (2020). Integration of R and Scala Using rscala. Journal of Statistical Software, 92(4), 1 - 18. doi:http://dx.doi.org/10.18637/jss.v092.i04

New Packages

📦 Go Live for More New Pkgs 📦

• January 2020: “Top 40” New R Packages

• RStudio Package Manager 1.1.2 - Windows

• opentripplanner: Fast and Easy Multimodal Trip Planning in R with OpenTripPlanner

CRAN

• relgam: Fitting reluctant generalized additive models

BioC

*GitHub or Bitbucket

• A new geom for ggplot, geom_bump shows rank over time

Updated Packages

• The next package release into AWS Athena

• digest 0.6.25: Spookyhash bugfix & RcppSimdJson 0.0.2: First Update!

• Nifty Upcoming Enhancements to unpack/to

• dbparser 1.1.0

• {searcher 0.0.5}

• {qualtRics 3.1.2}

Tutorials

• One liner to show all colours available in R

• Visualizing the Bayesian workflow in R

Incredibly clearly explained and visualised post on Bayesian technqieus using both brms and Stan

• Use regression, inverse probability weighting, and matching to close confounding backdoors and find causation in observational data

Another comprehensive guide to lesser-explained techniques, this time in understanding causal effects

• In this notebook run Monte Carlo simulations to estimate the volume of the d-dimensional ball.

• A curated list of awesome ggplot2 tutorials, packages etc.

Possibly the most complete guide to geoms there is. Extremely extensive and well organised

• BIMI Up, Scotty! A look at Brand Indicators for Message Identification (BIMI) Adoption with R and the Alexa Top 1m

• Synthetic micro-datasets: a promising middle ground between data privacy and data analysis

A really neat solution especially of use to people wanting to blog about their work but limited by privacy concerns

• Le Monde puzzle #1132

• multiplying the bars

• Cleaning Dirty Excel Sheets in R

• RStudio 1.3 Preview: Integrated Tutorials

• New xgboost defaults

• All you need to know on PCA …

• A New Baby Boom Poster

• Take a Sad Script & Make it Better: Tidymodels Edition Really neat examples showing different approaches (and pitfalls) to the same problem coupled with a dazzling array of penguin gifs

International R

Probabilidades de pasar la fase de grupos en Copa Libertadores 2020

R Project Updates

Updates from R Core:

• Kurt Hornik: stringsAsFactors

Upcoming Events in 3 Months

Events in 3 Months:

• Postgres Conference 2020 - Keynote! Time-to-Event Analytics: Probabilistic Programming with R and Stan (Malmö, Sweden), March 31

• satRday Johannesburg 2020

• satRday Newcastle upon Tyne, April the 4th, Call for speakers for #satRdayNCL closes 31st Jan.

• A list of R conferences and meetings

• This week’s local R-User and applied stats events

• satRday Neuchâtel 2020

More past events at R conferences & meetups.

Datasets

• A database of FIFA player attributes

Jobs

• R Studio Internships

Call for Participation

Your support will keep R Weekly team moving! 💡

### Quotes of the Week

Trying to reproduce a colleague's fish movement analysis by going through his #Rstats code. his code ends with this comment.

# Fuck this! I'm doing it manually pic.twitter.com/9LkWjX617I

— Peter Dudley (@BiophysicalEco) February 28, 2020

My new map shows 554 cases of partisan bridge and rail sabotage in the Independent State of Croatia during World War II.#insurgency #resistance #sabotage #history #Yugoslavia #rstats #dataviz #maps pic.twitter.com/2EeBos5faV

— Milos Popovic (@milos_agathon) February 28, 2020

Domain specific knowledge is crucial in #dataScience, this is my new favourite picture to illustrate why! You may be an absolute #rstats or #python ninja, but be sure to team up with a domain specialist if you find yourself in unknown territory 💻📊📈📉👍 pic.twitter.com/iqu3AMIOty

— Leon Eyrich Jessen (@jessenleon) February 19, 2020

The roundest municipalities in Brazil? Useless map done entirely in R. #rstats. Using geoBr::, tnks @UrbanDemog. Inspiration @AndriyYaremenko @tjukanov. pic.twitter.com/Gr0pqi4zxV

— Arthur Welle (@ArthurWelle) February 27, 2020