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
- Produce a reproducible report with a graph, map and tables
- Run this report on multiple times for different gift officers
- Schedule the report to run automatically
Our Tools
- R
- R Projects
- RStudio
- RMarkdown
- 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
