Pins

Sharing Data With the pins Package

The pins package publishes R objects, such as data sets and predictive models, on a virtual corkboard so that you can share and reuse them easily and safely

pins 1.0.0

pins 1.0.0 is now available on CRAN! The pins package publishes data, models, and other R objects, making it easy to share them across projects and with your colleagues. Pins can be versioned, making it straightforward to track changes, re-run analyses on historical data, and undo mistakes

Hadley Wickham

pins 0.4.0: Versioning

A new release of pins is available on CRAN today. This release adds support to time travel across dataset versions, which improves collaboration and protects your code from breaking when remote resources change unexpectedly

pins 0.3.0: Azure, GCloud and S3

New CRAN release for pins adds support for cloud boards (Azure, Google Cloud and S3), new functions, use cases and many other improvements

pins: Pin, Discover and Share Resources

RStudio Team

Katie Masiello || Build a Codenames app using {pins} and Shiny! || RStudio

00:00 Introduction 00:05 Project outline 03:56 Create a codename generator (using RMarkdown) 09:35 Publish to RStudio Connect 10:38 Create a Shiny app 18:15 A little bit of troubleshooting 18:18 Ta-da! Learn more about the pins package here: https://pins.rstudio.com/ Learn more about Shiny here: https://shiny.rstudio.com/ And learn more about RStudio Connect here: https://www.rstudio.com/products/connect/ Got questions? The RStudio Community site is a great place to get assistance: https://community.rstudio.com/ Content: Katie Masiello (@katieontheridge) Animation, motion design, and editing: Jesse Mostipak (@kierisi) Theme song: Contrarian by Blue Dot Sessions (https://app.sessions.blue/browse/track/64281)

RStudio's {pins} package: what it is, how it works, and what it can do for you! || RStudio

00:00 Introduction 00:09 What is the pins package? 01:49 pins - not just for RStudio Connect! 02:31 pins use cases 04:47 How to use pins instead of final_final_01_noreallyfinal.xls 06:37 How do pin boards work? 08:55 Getting started with pins 10:42 Versioning with pins at the board or pin level 11:47 pins and caching 12:13 Things you shouldn't pin 14:00 Major functions in the pins package 17:21 Using pin_upload( ) and pin_download( ) 19:52 pins and Google Cloud 21:27 pins and modelops with the vetiver package Learn more about the pins package here: https://pins.rstudio.com/ Got questions? The RStudio Community site is a great place to get assistance: https://community.rstudio.com/ Content: Katie Masiello (@katieontheridge) and Jesse Mostipak (@kierisi) Animation, motion design, and editing: Jesse Mostipak (@kierisi) Theme song: Contrarian by Blue Dot Sessions (https://app.sessions.blue/browse/track/64281)

Julia Silge | Monitoring Model Performance | RStudio

0:00 Project introduction 1:50 Overview of the setup code chunk 3:05 Getting new data 4:05 Getting model from RStudio Connect using httr and jsonlite 6:20 Bringing in metrics 9:45 Using the pins package 10:50 Using boards on RStudio Connect 13:30 Benefits of using pins 14:00 Visualizations using ggplot and plotly 17:00 Knitting the flexdashboard 18:10 Project takeaways You can read Julia's blogpost, Model Monitoring with R Markdown, pins, and RStudio Connect, here: https://blog.rstudio.com/2021/04/08/model-monitoring-with-r-markdown/ Modelops playground GitHub repo: https://github.com/juliasilge/modelops-playground pins package documentation: https://pins.rstudio.com/ flexdashboard documentation: https://rmarkdown.rstudio.com/flexdashboard/ tidymodels documentation: https://www.tidymodels.org/

Julia Silge

Javier Luraschi | Using pins with Python and JavaScript | RStudio

Last year, pins got released as a brand new R package to pin, discover and cache remote resources for R users. This package has matured to support many use cases; from caching remote URLs, and easily sharing datasets with other R users, to building automated pipelines. However, in order to truly collaborate in multi-disciplinary data-driven teams, one needs to consider how to collaborate beyond R. How can we share resources with designers and machine learning experts who happen to use different programming languages like Python and JavaScript? This talk will introduce the pinsjs project, a cross-language community project which has the goal of bringing pins to the broader open source community to enable rich workflows across larger data-driven teams. About Javier: Javier is the author of “Mastering Spark with R”, pins, sparklyr, mlflow and torch. He holds a double degree in Math and Software Engineer and decades of industry experience with a focus on data analysis. Javier is currently working on a project of his own; and previously worked in RStudio, Microsoft Research and SAP