R Weekly 2019-06 Workshop, Cookbook

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Hello and welcome to this new issue!

Highlight

• rstudio::conf 2019 Workshop materials now available

• BBC Visual and Data Journalism cookbook for R graphics

Insights

• The tidyverse style guide

• How Do You Tell What Packages To Trust?

• Organizing R Research Projects: CPAT, A Case Study

Resources

• rstudio::conf 2019 Workshop materials now available

• What They Forgot to Teach You About R - Jennifer Bryan, Jim Hester

• An Overview of the NLP ecosystem in R

R in the Real World

• Just How Liberal Are the 2020 Democratic Candidates?

• Send UDP Probes (with payloads) and Receive/Process Responses in R

• Zipf’s law is an empirical law that states that many different datasets found in nature can be described using Zipf’s distribution.

• Multiple Data (Time Series) Streams Clustering

• A package to download, import and tidy time series data from the Australian Bureau of Statistics

• Developing a package to analyze data of the hospital morbidity survey

• Retail Data Visualization with R and Shiny

• Building Our Own Open Source Supercomputer with R and AWS

R in Organizations

• RC RUGS 2019 Is Up and Running

• BBC Visual and Data Journalism cookbook for R graphics

R in Academia

New Packages

? Go Live for More New Pkgs ?

CRAN

• tsfeatures - provides methods for extracting various features from time series data.

• readabs - Download, import, and tidy time series data from the Australian Bureau of Statistics

• olsrr - a set of tools for improved output from linear regression models, designed keeping in mind beginner/intermediate R users.

GitHub or Bitbucket

• whiteboxR - whitebox R package for geospatial analysis, which is an R frontend of a stand-alone executable command-line program called WhiteboxTools

• shutterstock-r - Access Shutterstock API from R

Updated Packages

• V8 2.0 - Embedded JavaScript Engine for R

• purrr 0.3.0

• cartography 2.2.0

Gist & Cookbook

• BBC Visual and Data Journalism cookbook for R graphics

Tutorials

• Audio classification with Keras: Looking closer at the non-deep learning parts

• Enhancing gather() and spread() by Using “Bundled” data.frames

• Benchmarking an Rstats workstation - using benchmarkme

• Introduction to Object Oriented Programming using S3 classes. German language. Make R play Rock - Paper - Scissors with user defined output (print method).

• Solving Ordinary Least Squares Regression Using Matrix Algebra in R

• Function Objects and Pipelines in R

• How to urn inconsistently multi-headered excel data into a tidy data frame in R.

• A little trick for debugging Shiny

• The power of tapping into your community for support

• 8 out of 10 cats does countdown

• Using the uniform sum distribution to introduce probability

• PDSwR2: New Chapters!

• trailing commas

Upcoming Events in 3 Months

Events in 3 Months:

• satRday Paris - 23rd February

• satRday Johannesburg - 6th April

• satRday Newcastle - 6th April

• satRday Los Angeles - 6th April

• 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

Finally out! Excited to announce my new book on statistical learning with @kaneplusplus and Bryan Lewis on @CRCPress. Code, data, and sample chapters available at https://t.co/iGSWS77oXy #rstats pic.twitter.com/ihAAcK5kmd

— Taylor Arnold (@statsmaths) February 8, 2019

When you read 2017 a scientific paper and everyone is cited except the authors of the free software used to do the research ? #rstats pic.twitter.com/0RCWOIlJrp

— Mark van der Loo (@markvdloo) February 6, 2019

Introducing pupR: Your Daily Dose of Doggo! Do you like dogs? Do you like R? Then you’ll love this function. #rstats #dogs pic.twitter.com/k3bW7RKAtP

— Melissa Innerst (@mathematicalm3l) January 30, 2019

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