R Weekly 2019-40 fable, lintr 2.0.0, almanac

07 Oct 2019

Release Date: 2019-10-07

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

Highlight

• Introducing {fable}: Forecasting models for tidy time series

• {lintr 2.0.0}: Checks adherence to a given style, looks for syntax errors and possible semantic errors

• {almanac}: Implements a ‘grammar of schedules’, providing the fundamental building blocks to construct recurrence rules that identify “events” such as weekends or holidays

Insights

• EARL London 2019 Conference Recap

• Why R? Warsaw 2019 Recap

R in the Real World

• Mapping the Underlying Social Structure of Reddit

• A Guide to Getting International Statistics into R

R in Organizations

• Business AI for SMBs - Building Amazon-style Product Recommenders using RemixAutoML

Resources

• {ggplot2} theme for Breast Cancer Awareness: theme_bc_aware

• Material for COMBINE NSW Workshop on R Markdown

New Packages

📦 Go Live for More New Pkgs 📦

CRAN

• {signs 0.1.0}: Provides convenience functions to replace hyphen-minuses (ASCII 45) with proper minus signs (Unicode character 2212)

• {fable}: Forecasting models for tidy time series

GitHub or Bitbucket

• {tune}: facilitate the tuning of hyper-parameters in the tidymodels packages

• {fastpipe}: fast alternative to {magrittr} pipes

• {almanac}: Implements a ‘grammar of schedules’, providing the fundamental building blocks to construct recurrence rules that identify “events” such as weekends or holidays

Updated Packages

• {geohashTools 0.3.0}

• {data.table 1.12.4}

• {tensorflow 2.0.0}

• {lintr 2.0.0}: Checks adherence to a given style, looks for syntax errors and possible semantic errors

• {geospark 0.2.1}

• {countup}: counter for RMarkdown & Shiny

• {lorem}: Quickly generate lorem ipsum placeholder text

Videos and Podcasts

• #TidyTuesday Podcast #6: School Diversity Data

• #TidyTuesday Screecast: Analyzing pizza ratings

• Intro to GeoSpatial Data in Spark

Tutorials

• Insights from the RMarkdown whisperer

• Flow fields (12 Months of aRt, September)

• Manipulating colors with {prismatic}

• Goodbye, Disqus! Hello, Utterances!

• theme_inari()

• Cox PH with Time varying Covariate, Part I

• A short introduction to {drake}

• Building Regularized Logistic Regressions from Scratch with Computational Graphs in R

• Split-apply-combine for Maximum Likelihood Estimation of a linear model

• Introducing {fable}: Forecasting models for tidy time series

R Project Updates

Updates from R Core:

Upcoming Events in 3 Months

Events in 3 Months:

• Tokyo.R #82, October 26

• Yes We Cran: A conference on R packages and their applications, December 6-8

• rOpenSci OzUnconf, December 11-13

• R @ ISSA, December 26

• A list of R conferences and meetings

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

More past events at R conferences & meetups.

Call for Participation

Your support will keep R Weekly team moving! 💡

Quotes of the Week

For those who use #dplyr but don't master it yet, we've just created for you the ultimate guide to the 1 tibble case in a single cheat sheet. Feedback appreciated!
Source = https://t.co/ucFHHFtCqV#tidyverse #rstats
Many tanks to Colin Vullioud for helping! pic.twitter.com/WISUiG4oST

— R Data Berlin (@rdataberlin) September 27, 2019

Learned last week from the man himself (JJ Allaire) that you can execute Python scripts in RStudio and it just *knows* #rstats (the first reticulate command auto-ran) pic.twitter.com/WdX8Evzqwg

— Hilary Parker (@hspter) September 30, 2019

ever want to join a list of dataframes together (with #rstats) in one fell swoop? try purrr::reduce(list_of_dfs, full_join, by = "id_column_name")

honestly, when this worked, i nearly cried

— renata gerecke (@renatagerecke) October 1, 2019