This blog will walk through my final Dashboard Week project, where I made the following dashboard, which can be found on Tableau Public here:
For DS44's final Dashboard Week project, we needed to participate in Tableau's Data + Movies challenge. The data is from IMDb, and tells us about ratings and voting of movies. I wanted to focus on a question that has intrigued me for a while:
Does looking like Matt Damon give you a better chance in Hollywood?
To decide on who looks like Matt Damon, I used an IMDb discussion on the topic. The actors in question are now:
- Matt Damon (certainly looks like Matt Damon...)
- Mark Wahlberg
- Tim Robbins
- Neal McDonough
I made some notes and sketches about what I wanted to achieve, and realised that I wanted to lean into the conceptual idea of a reflection, and create a butterfly-chart inspired line chart comparison. I would combine it with an image of a body of water's surface to give the impression that the line is being reflected, with Matt Damon being above and the lookalikes being below.
With this in mind, I started building. To be able to place my graph over a water line, I needed to both create a measure which reflects for the lookalikes and create a graph which the zero line remains centred. My solution was to have invisible lines behind the main graph which fix the axis.
Now if I change the focus to another actor or change any measures, the zero line will remain in the same place - allowing me to ensure that my visuals do not get misaligned!
Since the focus of the dashboard is on Matt Damon, I needed to verify that Matt Damon is indeed successful using the data. I decided to do this in a second section:
Under the surface
In this section of the dashboard, I look into what Matt Damon is doing differently to his lookalikes. The section is literally placed under the water surface that the previous section was in, and so I continued with this theme by making the section a dark theme - mimicking deep sea exploration.
Here I found that Matt Damon had the most films overall, most films per year, and the least spread of genres out of his lookalikes.