brendanjodowd / cso

R Package for CSO data tables

Hi there 👋

I am a Senior Statistician at the Central Statistics Office (CSO). I use GitHub for a couple of work-related and hobby projects. My main languages are R and SAS.

Some projects

• My GitHub Pages site where I have guides for making maps and implementing statistical disclosure controls.
• 🎓 Higher Education Outcomes - a longitudinal study of outcomes for higher education graduates carried out using admin data.
• 🌐 Ireland maps - a collection of compatible maps produced using shapefiles from OSi and OSNI and the rmapshaper package.
• 💑 SAS-R Cheatsheet - a guide to learning R for SAS users, or vice versa. Now hosted on the RStudio website.
• 📈 R Package for importing data from CSO Statbank - This has been superseded by an official CSO package.
• 👨‍👩‍👧‍👦 LEA Population Map - A Shiny web app to calculate population in selected LEAs
• 🍫 The Axis of Fudge - Another Shiny project to interactively examine and compare brownie recipes
• 🔧 SAS Macros - a ton of macros for SAS that I developed/collected over the years

You can find me on LinkedIn here.

cso's Issues

.gitignore not ignoring user files/folders

Nice work Bren!

Just a quick spot on the repo itself - .gitignore probably shouldn't sync the following since they're not necessary for the build:

.Rproj.user/
.Rbuildignore
.Rhistory

I think you need the trailing slash to ignore folders, and to purge previously tracked files, you can use
git rm --cached FILENAME

This is a really handy package though, well done! For example, off topic, but playing around with the driving test dataset (code "ROA07") shows an interesting trend:

That spike is where they brought in the N-plate restriction, which must have been fairly mental in the testing centres! But if you look at the pass percentage, for that year it actually went up, but then dropped precipitously, almost like the testers were told they had passed too many new drivers in 2008...!

(code for these plots:

library(CSO)
library(ggplot2)
library(reshape2)

dtest.data <- get_cso("ROA07")

dtest.wide <- dcast(dtest.data, Year + Age.Group ~ Statistic, value.var = "value")

ggplot(dtest.wide, aes(Year, `All Driving Tests (Number)`)) + geom_line(aes(color=as.factor(Age.Group), group=as.factor(Age.Group)))
ggplot(dtest.wide, aes(Year, `Percentage of Driving Tests Passed (%)`)) + geom_line(aes(color=as.factor(Age.Group), group=as.factor(Age.Group)))

)