- R Markdown is just great for static reports. We use PowerBI or ArcGIS for interactive stuff.
- GIS is a breeze. My work provides licenses for ArcGIS, which has a Python library for scripting. Despite that, it is so much easier to do stuff in R, which can read and create ArcGIS shapefiles.
- Exploratory data analysis is easy. Often, before meetings, I'll connect to the database in R and make a few basic tables. Then I can query, aggregate, or plot data sitting the meeting. I have custom ggplot themes in a package, so even my happy hastily created plots look nice.
- RStudio is amazing. What it lacks in editing tricks, it more than makes up for in simplifying R-specific tasks. Showing plots is automatic, rendering and viewing markdown reports (of any type) is two buttons, testing and building a package are each two buttons.
- I spent a lot of time evangelizing R (team-wide presentations, being the "R guy" for troubleshooting, organizing an R User Group with members from different teams, creating an internal package repository). Some became happy converts, the rest begrudgingly accepted it as a tool we would use. I don't know if I could do it again with another language.
I'll admit my work doesn't get incorporated into pipelines. We get the data, analyze it, create reports, and share the reports by email or on our public website. The statisticians are segregated from the developers here. State government resists change, especially role changes that don't match grants' or laws' wording.
Quarto (also supporting R) is a good replacement for rmarkdown (with a saner syntax) and I say this as someone who has extensively used rmarkdown over the years.
- R Markdown is just great for static reports. We use PowerBI or ArcGIS for interactive stuff.
- GIS is a breeze. My work provides licenses for ArcGIS, which has a Python library for scripting. Despite that, it is so much easier to do stuff in R, which can read and create ArcGIS shapefiles.
- Exploratory data analysis is easy. Often, before meetings, I'll connect to the database in R and make a few basic tables. Then I can query, aggregate, or plot data sitting the meeting. I have custom ggplot themes in a package, so even my happy hastily created plots look nice.
- RStudio is amazing. What it lacks in editing tricks, it more than makes up for in simplifying R-specific tasks. Showing plots is automatic, rendering and viewing markdown reports (of any type) is two buttons, testing and building a package are each two buttons.
- I spent a lot of time evangelizing R (team-wide presentations, being the "R guy" for troubleshooting, organizing an R User Group with members from different teams, creating an internal package repository). Some became happy converts, the rest begrudgingly accepted it as a tool we would use. I don't know if I could do it again with another language.
I'll admit my work doesn't get incorporated into pipelines. We get the data, analyze it, create reports, and share the reports by email or on our public website. The statisticians are segregated from the developers here. State government resists change, especially role changes that don't match grants' or laws' wording.