R Weekly 2020-42 Climate animation, NNMF in soccer, and Raspberry Pi with R

19 Oct 2020

Release Date: 2020-10-19

This week’s release was curated by Ryo Nakagawara, with help from the RWeekly team members and contributors.

• How to have (my) content shared by R Weekly?

Highlight

• Climate animation of maximum temperatures

• Decomposition and Smoothing with data.table, reticulate, and spatstat

• Raspberry Pi E-Paper Dashboard with R

Insights

• R 4.0.3 now available

• Submitting R package to CRAN

• RStudio v1.4 Preview: Command Palette

• rstudio::global (2021)

• 2 Months in 2 Minutes - rOpenSci News, October 2020

• My year in R

R in the Real World

• Raspberry Pi E-Paper Dashboard with R

• Decomposition and Smoothing with data.table, reticulate, and spatstat

• World Cup Birthday Problem

• Scoring doesn’t Stop? Looking at the trend of high scoring games in the EPL

• Climate animation of maximum temperatures

• Covidpreprints.com: Automating Website Updates with the europepmc and rAltmetric Packages

• How to: Download and Animate Polar Ice Data in R with Rayrender

Resources

• Daily Portuguese COVID-19 Data

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• {giscoR} 0.1.0: Download Geospatial Data from GISCO - Eurostat on several resolutions and projections.

• {qqr} 0.0.1: Data from Brazilian Soccer Championship.

• {survivalmodels} 0.1.0: Models for Survival Analysis.

• {shinypanel} 0.1.2: Shiny Control Panel.

• {anscombiser} 1.0.0: Create Datasets with Identical Summary Statistics.

• {gsisdecoder} 0.0.1: High Efficient Functions to Decode NFL Player IDs.

• {cdcfluview} 0.9.2: R package to Retrieve U.S. Flu Season Data from the CDC FluView Portal (WHO & ILINet).

GitHub or Bitbucket

• {flipdownr} 0.1.0: Create a Countdown object within your RMarkdown documents and Shiny application.

• {terrainr}: Retrieve Data from the ‘USGS’ National Map and Transform it for ‘3D’ Landscape Visualizations.

• {typed}: Experiment on static typing in R.

• {reactor}: Unit testing for shiny reactivity.

• {geomlime}: Provides a bloody geom_lime() function for ggplot because of all the zarking times I frakking type geom_lime() instead of geom_line().

• {rockthemes}: This is a collection of colour palettes based on classic rock album covers.

• {flipdownr}: Create a CountDown in Rmarkdown Documents and Shiny Apps.

• {tidyCpp} 0.0.1: Tidy C++ wrapping of the C API for R.

• {purler}: fast run-length encoding with data.frame output.

• {Manu}: This function returns colour palettes derived from birds native to New Zealand.

Updated Packages

• {rrapply} 1.2.0: Revisiting Base rapply().

• {udpipe} 0.8.4-1:

• {echarts4r} 0.3.3: ECharts 4 for R.

• {gert} 1.0.2: Simple git client for R.

• {r2mlm}: R-Squared Measures for Multilevel Models.

• {brms} 2.14.0: R package for Bayesian generalized multivariate non-linear multilevel models using Stan.

• {tidyBF} 0.4.0.9000: Tidy wrapper around BayesFactor R package.

• {politeness} 0.7.0: Detecting Politeness Features in Text.

• {openSTARS} 1.2.2: An Open Source Implementation of the ‘ArcGIS’ Toolbox ‘STARS’.

• {rqdatatable} 1.2.9: ‘rquery’ for ‘data.table’.

• {h2o} 3.32.0.1: R Interface for the ‘H2O’ Scalable Machine Learning Platform.

• {magick} 2.5.0: Advanced Graphics and Image-Processing in R.

• {checkdown} 0.0.6: Check-Fields and Check-Boxes for ‘rmarkdown’.

• {gganimate} 1.0.7: A Grammar of Animated Graphics.

• {censusapi} 0.7.1: Retrieve Data from the Census APIs.

• {e1071} 1.7-4: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien.

• {DT} 0.16: A Wrapper of the JavaScript Library ‘DataTables’.

• {pagedown} 0.12: Paginate the HTML Output of R Markdown with CSS for Print.

• {NIMBLE} 0.10.0: The base NIMBLE package for R.

• {dang} 0.0.12: A collection of utility functions for R.

Videos and Podcasts

• R Programming for Beginners / How to Merge Datasets Using BaseR!

• Predict class membership for the Datasaurus Dozen with tidymodels

• TidyX Episode 32

Shiny Apps

• Player ProfileR: Create your own beeswarm plots for any stat you want for players in Europe’s top 5 football leagues

Tutorials

• Recursive apply for call and expression objects

• R Markdown: Automatically render output on saving file

• udpipe R package updated

• Introducing {waldo}

• Dive into dplyr (tutorial #1)

• Feature Engineering with Sliding Windows and Lagged Inputs

• sparklyr.flint 0.2: ASOF Joins, OLS Regression, and additional summarizers

• ANOVA in R

• Finding the Dimensions of secdatabase.com from 2010-2020 - Part 2

• Display Pretty R tables in GitHub

• simstudy just got a little more dynamic: version 0.2.1

• Finding the Shortest Path with Dijkstra’s Algorithm

• Predicting class membership for the #TidyTuesday Datasaurus Dozen

• Spatial Data Analysis Using Artificial Neural Networks, Part 2

• Fermat’s Riddle

• Little useless-useful R function

• R: Add a Column to Dataframe Based on Other Columns with dplyr

International R

• (Japanese) R MarkdownでHTML出力時に見出しのURLを簡単に取得できるようにした

R Project Updates

Updates from R Core:

Upcoming Events in 3 Months

Events in 3 Months:

• Nairobi R: Data Visualization in R online workshop. Oct. 31

• SatRday Columbus - Free virtual conference on November 14

• rstudio::global (2021)

• A list of R conferences and meetings

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

Call for Participation

Your support will keep R Weekly team moving! 💡

### Quotes of the Week

I'm gonna start a thread on what I hope will be helpful R tips to wrangle this huge NFL Big Data Bowl data. If you're an advanced R programmer, this is probably not for you but feel free to correct me if I made a mistake or offer better alternatives

— Asmae Toumi (@asmae_toumi) October 17, 2020

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">late night <a href="https://twitter.com/hashtag/tidytuesday?src=hash&amp;ref_src=twsrc%5Etfw">#tidytuesday</a> submission..i just couldn&#39;t wrap my head around the fact that indeed, those points really &quot;end up&quot; with the same mean and standard deviation. so i plotted it to convince myself. :) <a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/ggplot?src=hash&amp;ref_src=twsrc%5Etfw">#ggplot</a> <a href="https://t.co/O2IoSPmCou">pic.twitter.com/O2IoSPmCou</a></p>&mdash; Frie (@ameisen_strasse) <a href="https://twitter.com/ameisen_strasse/status/1316133566972125186?ref_src=twsrc%5Etfw">October 13, 2020</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> 
  
  <blockquote class="twitter-tweet"><p lang="en" dir="ltr">This is cool <a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a>! str_replace() takes a `pattern` to find in text and a `replacement` that it puts in place of the found text. But give `replacement` a function and str_replace() applies the function to each match!<br><br>Ex: turn &quot;1/2&quot; into a decimal by evaluating -&gt; &quot;0.5&quot; <a href="https://t.co/ehkGunTmpH">pic.twitter.com/ehkGunTmpH</a></p>&mdash; Garrick Aden-Buie (@grrrck) <a href="https://twitter.com/grrrck/status/1317540828580106240?ref_src=twsrc%5Etfw">October 17, 2020</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>