Day four of Dashboard week saw DSAU5 working with US Consumer spending between 1959 to 2018. The data provided an eight-level hierarchy and our challenge was to firstly clean the aggregation in the data, normalize the data, and as always make an interesting story out of the data.
Alteryx Component:
Cleaning the aggregation had a level of interpretation, which forced group collaboration between the group early on, while also needing to decide which inflationary numbers to use, and the best approach for comparison. I decided to aggregate the data to the yearly level. In our normalizing discussion, discounted methods were proposed, but I went ahead with creating a real growth rate, but reducing a calculated growth rate from us spending, and subtracting the yearly inflation rate. I went ahead with this approach because what I wanted to focus on was trends between years. The following Alteryx workflow was used to create this real growth equation:
This process was repeated for both the yearly grain, and level 1, 2 and 3 grain, but for my final visualization, I focused on the level 3 grain. I also found some population statistics to incorporate population growth and subtracted that from the real growth rate. This was done in the following process before the subtraction join:
Tableau Component:
With Adjusted Real Growth Rates, the most suitable chart would be a line chart, but even so, I decided I wanted to do something different, so I went to google and searched for “Cool Line Charts” for instance, and found a blog by vizzing data http://www.vizzingdata.com/visualizing-radial-time-series-data-to-uncover-patterns-in-tableau/. I found my inspiration.
I followed their general steps to creating the chart but got to a cross-roads. Firstly I had negative growth rates and secondly, I wanted to show my data at a yearly grain, and at a Level 3 grain with the growth rates, and quite frankly it was a little hard to see the patterns. So I decided to make the graphs changeable using parameters: i.e., instead of having the Year(Year) and Level 3 in the separate equations, I created 1 parameter, and 2 equations for the interchanging of that parameter to swap between the dot columns being years and level 3 category. In hindsight, I see this chart to be very effective if you had 6 – 10 categories, but I had too many which made comparisons much more difficult. I decided to create custom bins to use in color to make the comparisons more visual, but I can see now why messing with position and size is usually a bad idea in visualization with many categories.
Unfortunately, when my parameters were made, there was a critical problem: the gaps were not in the same position. So, the only solution I could think, where the floating object in the view will be the same as if I made 2 sheets. I could then use parameters potentially to swap between the sheets, but I decided to go back to Tableau basics and use a button to swap between dashboards, to make the appearance of a changing sheet.
Concluding Comment:
This graph looks very interesting and unique but I can never see myself using this chart in a practical application. Nonetheless, I feel for this instance you can derive some value in the colour and supplementary bars. After all my hard work in the day, my dashboard ended up looking like;
