Hey everyone, welcome to Dashboard Week day 1 for the Data School Down Under cohort 10!!!
I’m writing this at 1:23am, so I’ll make it brief. For those of you who don’t know, Dashboard Week is a tradition in the Data School where analysts-in-training create a dashboard (and write a blog about it) once a day for a week.
Today everyone was assigned an Australian government dataset of registered charities. The data was quite clean, with most of the problems being a result of charities filling in information incorrectly. For example, someone put down the primary state of their charity as “South Austalia.”
There was also one instance of a charity claiming that they were headquartered in “Melbourne, Austria.” Maybe there’s a different Melbourne in the Alps? Tidying up these errors was quite straightforward, and required only a basic Alteryx workflow.
As is often the case, the hardest part was figuring out interesting relations in the data, and how to present these relations. I initially considered a simple overview of how charity types are distributed by state, and then made the concept a little more sophisticated by focusing on not the absolute count of charities by state, but rather whether a particular type of charity is overrepresented or underrepresented in a particular state relative to the whole of Australia. I envisioned a dashboard that could provide useful information for someone looking to start a charity. Charities for women, as an example, might be more common per capita in one state than another. An enterprising charity founder might benefit from going where communities are underserved. My final product looks like this:
Clicking on a particular charity type also brings you to a drill-through dashboard with stats filtered accordingly:
If you’d like to play around with this viz, it’s on Tableau Public here.
