Optimizing your Data Science Workflow in R

Slides and materials on GitHub: https://github.com/majerus/NEDRA2018

Follow along today: https://goo.gl/V7NMhL 

R is a free open-source statistical software.

RStudio is an interface to using R.

Shiny deploys R code on the web. 

A few definitions...

RMarkdown weaves text and code into reports. 

Our Goals

  1. Produce a reproducible report with a graph, map and tables
  2. Run this report on multiple times for different gift officers
  3. Schedule the report to run automatically

 

Our Tools

  1. R
  2. R Projects
  3. RStudio
  4. RMarkdown
  5. Cron | taskscheduleR

RMarkdown 

Our R Project

Scheduling Unserved Approaches

Windows: taskscheduleR

Mac: cron

A Shiny Approach

A Shared Data Approach

Crosstalk and Shared Data

  • Linked interactive visualizations
  • Filtering and personalization capability
  • No server required

Where to go from here

Credits

 Madebyoliver from Flaticon licensed by Creative Commons BY 3.0

 smashicons from Flaticon licensed by Creative Commons BY 3.0

 Freepik from Flaticon licensed by Creative Commons BY 3.0

 Freepik from Flaticon licensed by Creative Commons BY 3.0

 Dave Gandy from Flaticon licensed by Creative Commons BY 3.0

 smashicons from Flaticon licensed by Creative Commons BY 3.0

 photos from unsplash.com

A word of inspiration...

NEDRA: Optimizing your Data Science Workflow in R

By Rich Majerus

NEDRA: Optimizing your Data Science Workflow in R

Optimizing your Data Science Workflow in R - a 2018 NEDRA workshop by Rich Majerus

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