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It’s the last day of Dashboard Week at The Data School Down Under. It was great knowing that we survived the previous 4 challenging days and produced some creative dashboards, practicing what we’ve learned and expanding our horizons through experimentation. On the other hand, I felt a bit sad knowing that it’s the last day of this fun concept and who knows when will be the next time when I will have the creative freedom to play with weird data sets – such as this one – Public Toilets across Australia.

Instead of working with data for all Australia I narrowed the scope and built a story about going on a road trip from Sydney to Gold Coast. I did this 11-hour long trip a while ago, so why not doing a dashboard this time about the public toilets along the way ?.

After applying some Alteryx massaging to the data, I was ready to continue with Tableau.

Using the lasso select tool I created one big group of all the plotted dots on the map that are close to the coast line and the roads between the two cities. This I used for the map on the dashboard.

The other part of the dashboard was consisted of BANs and two waffle charts. I like the simplicity of the waffle charts and how easily they convey messages related to part-to-whole data. There is great tutorial on doing a waffle chart here. Basically, this is what I did to get the final look.

• Created a spreadsheet in excel that I used as the basis for the waffle. (Yes, excel is a helpful tool.)

• I brought in Tableau this and the original data source and started creating the waffle using the excel spreadsheet shown above. It’s as easy as – putting columns on columns, rows on rows and disaggregating the data using the Analysis drop-down menu.

• Next is creating the calculations that will color the percentage of dots we are interested in. Since I was interested in the proportion of Accessible toilets out of all, I had to identify them through a calculation:

if [Accessibility]=’Yes’ then [Toilet ID] else null end

• And for calculating the proportion I used a fixed level of detail calculation because my data had more than one row per public toilet. I was dividing the distinct number of accessible toilets with the distinct number of all toilets. I additionally used the rounding option so that I have the precision I needed when plotting the percentages on the waffle.

{FIXED  : round( COUNTD([ACCESSIBLE TOILETS])/COUNTD([Toilet ID]),2)}

• Going back to the waffle data set I created one additional calculation that was connecting both data sets and was defining the number of dots that need to be colored based on the previously calculated proportion. One thing to note here is that it wasn’t necessary to define the blend.

• When we drag this calculation to the color marks card we get the following view:

• With some additional formatting I was able to achieve the final look that I incorporated in my day 5 dashboard.

With this one created on Friday – I can say that we closed this fun Dashboard week chapter. Now heading to new data adventures.