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R Weekly 2023-W20 ggflowchart, Dockerized Development Environments, Production is like Ultra Running
This week’s release was curated by Sam Parmar, with help from the R Weekly team members and contributors.
Highlight
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Why you should consider working on a dockerized development environment
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Colin Fay, Keynote: Production is like ultra running: brutal, ungrateful, but worth every step
Insights
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Pledging My Time VI: scraping and analysis of race results in R
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Bootstrap Intervals: Understanding the Gender-based Over-qualified Rates
R in the Real World
R in Organizations
R in Academia
Resources
New Packages
CRAN
- {annmatrix} 0.1.1: Annotated Matrix: Matrices with Persistent Row and Column Annotations
- {ggflowchart} 1.0.0: Flowcharts with ‘ggplot2’
- {pressuRe} 0.1.0: Imports, Processes, and Visualizes Biomechanical Pressure Data
- {OHCSpackage} 0.1.5: Prepare Housing Data for Analysis
- {iplookupapi} 0.1.0: Client for the ‘iplookupapi.com’ IP Lookup API
- {ipbase} 0.1.1: Client for the ‘ipbase.com’ IP Geolocation API
- {emailvalidation} 0.1.0: Client for the ‘emailalvalidation.io’ E-Mail Validation API
- {NLPutils} 0.0-5.1: Natural Language Processing Utilities
- {qdap} 2.4.6: Bridging the Gap Between Qualitative Data and Quantitative
- {qdapTools} 1.3.7: Tools for the ‘qdap’ Package Analysis
- {modACDC} 1.0.0: Association of Covariance for Detecting Differential Co-Expression
- {ggtricks} 0.1.0: Create Sector and Other Charts Easily Using Grammar of Graphics
- {ISAR} 0.1.10: Introduction to Sports Analytics using R (ISAR) Data
- {WCluster} 1.1.0: Clustering and PCA with Weights, and Data Nuggets Clustering
- {shiny.exe} 0.1.0: Schedule a Task that Runs a shinyApp then Creates a Shortcut in Current Directory
- {fetch} 0.1.2: Fetch Data from Various Data Sources
- {StockDistFit} 1.0.0: Fit Stock Price Distributions
- {ggplot2.utils} 0.2.1: Selected Utilities Extending ‘ggplot2’
- {tutorial.helpers} 0.2.3: Helper Functions for Creating Tutorials
- {ggrounded} 0.0.3: Rounded Bar Plots
- {covid19br} 0.1.5: Brazilian COVID-19 Pandemic Data
- {tidytlg} 0.1.1: Create TLGs using the ‘tidyverse’
- {SSplots} 0.1.1: Stock Status Plots (SSPs)
- {shiny.telemetry} 0.1.0: ‘Shiny’ App Usage Telemetry
- {rfars} 0.3.0: Download and Analyze Fatal Crash Data
- {survstan} 0.0.1: Fitting Survival Regression Models via ‘Stan’
Updated Packages
- {nanonext} 0.8.3: R binding for NNG (Nanomsg Next Gen), a successor to ZeroMQ.
- {fairml} 0.8: Fair Models in Machine Learning - diffify
- {ggdist} 3.3.0: Visualizations of Distributions and Uncertainty - diffify
- {pROC} 1.18.2: Display and Analyze ROC Curves - diffify
- {colorblindcheck} 1.0.2: Check Color Palettes for Problems with Color Vision Deficiency - diffify
- {stringstatic} 0.1.1: Dependency-Free String Operations - diffify
- {VeryLargeIntegers} 0.2.1: Store and Operate with Arbitrarily Large Integers - diffify
- {MCMCvis} 0.16.0: Tools to Visualize, Manipulate, and Summarize MCMC Output - diffify
- {softbib} 0.0.2: Software Bibliographies for R Projects - diffify
- {reporter} 1.4.1: Creates Statistical Reports - diffify
- {rhino} 1.3.1: A Framework for Enterprise Shiny Applications - diffify
- {confintr} 1.0.1: Confidence Intervals - diffify
- {tuneR} 1.4.4: Analysis of Music and Speech - diffify
- {rviewgraph} 1.4.2: Animated Graph Layout Viewer - diffify
- {AirMonitor} 0.3.11: Air Quality Data Analysis - diffify
- {parquetize} 0.5.6.1: Convert Files to Parquet Format - diffify
- {daterangepicker} 0.2.0: Create a Shiny Date-Range Input - diffify
- {nonmemica} 1.0.1: Create and Evaluate NONMEM Models in a Project Context - diffify
- {contingencytables} 2.0.0: Statistical Analysis of Contingency Tables - diffify
- {flashlight} 0.9.0: Shed Light on Black Box Machine Learning Models - diffify
- {finalsize} 0.2.0: Calculate the Final Size of an Epidemic - diffify
- {bookdown} 0.34: Authoring Books and Technical Documents with R Markdown - diffify
- {simplevis} 7.1.0: Wrappers to Simplify ‘leaflet’ Visualisation - diffify
- {waldo} 0.5.1: Find Differences Between R Objects - diffify
- {httr} 1.4.6: Tools for Working with URLs and HTTP - diffify
- {data.validator} 0.2.0: Automatic Data Validation and Reporting - diffify
- {VedicDateTime} 0.1.4: Vedic Calendar System - diffify
- {ShinyItemAnalysis} 1.5.0: Test and Item Analysis via Shiny - diffify
- {ctrdata} 1.13.1: Retrieve and Analyze Clinical Trials in Public Registers - diffify
- {IncidencePrevalence} 0.3.0: Estimate Incidence and Prevalence using the OMOP Common Data Model - diffify
- {RNewsflow} 1.2.7: Tools for Comparing Text Messages Across Time and Media - diffify
- {parabar} 1.1.0: Progress Bar for Parallel Tasks - diffify
- {reproducible} 2.0.2: Enhance Reproducibility of R Code - diffify
Videos and Podcasts
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Colin Fay, Keynote: Production is like ultra running: brutal, ungrateful, but worth every step
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Nicola Rennie: Finding #RStats resources with Shiny and GitHub Actions
Shiny Apps
R Internationally
Tutorials
R Project Updates
Updates from R Core:
R Contributor Office Hours, Thursday May 11: Europe/Middle East/Asia-Pacific Hour or Americas Hour
Join an online Office Hour at the time that suits you to:
- discuss how to get started contributing to R
- get help/feedback on contributions you are working on
- look at open bugs/work on translations together
Upcoming Events in 3 Months
Events in 3 Months:
Jobs
💼 Explore Jobs & Gigs Board on RStudio Community 💼
rtistry
A population density map of the Pearl River Delta. Couldn't decide which one I like better so here's both. The left one includes Hong Kong; the one on the right doesn't and is bound to the shape of the actual delta. Which one do you prefer?#rayshader adventures, an #rstats tale pic.twitter.com/xbfV2ZXIU7
— terence t (@researchremora) May 12, 2023
🔍 Explore the hidden secrets of urban layouts with #rstats! Analysing street orientation the #rspatial way includes just a few lines of code to come up with this plot for every city on earth.
— Marco Sciaini (@shinysci) May 10, 2023
💾 gist: https://t.co/JASpUSBSkf… #gischat pic.twitter.com/3o0B9Ks6pg
Monochrome Trigonometry 709
— aRtfulBot (@aRtfulBot) May 14, 2023
Done in #rstats with #ggplot2#Rtistry #generativeart #creativecoding pic.twitter.com/hEEtnGeYbU